[mlpack] annotated tag debian/2.0.0-1 created (now 08e020d)
Barak A. Pearlmutter
barak+git at pearlmutter.net
Mon Jan 18 16:43:24 UTC 2016
This is an automated email from the git hooks/post-receive script.
bap pushed a change to annotated tag debian/2.0.0-1
in repository mlpack.
at 08e020d (tag)
tagging 98569b11f4aa9c229282f0b34f9123158e3d3c2a (commit)
replaces debian/1.0.12-5
tagged by Barak A. Pearlmutter
on Mon Jan 18 16:39:56 2016 +0000
- Log -----------------------------------------------------------------
mlpack Debian release 2.0.0-1
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(no author) (3227):
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commit e9f9cdebf8e11120fddde9278ab146aa16b542d3
Redundant copy optimization in MPI_Alltoallv.
Fix to the FindSubTable function. Iterator is not erased, but now the front object is put to the position that is replaced.
commit 4d5e10e4729feb3ee2a70df9ed6b442a2fb53e5b
Minor fix.
more work.
More progress.
Some changes.
More cleanups.
Fixing compile error.
Bug fixed.
More documentations added.
Done for tonight.
Really done.
Minor changes.
Removed math::Pow from bounds_aux.h
Added support for cmath in fastlib.h
converted general_type_bounds.h to using std::pow
More documentation added.
Changed contrib files using Math::Pow to std::pow and std::sqrt
changed fastlib files using Math::Pow to std::pow and std::sqrt
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Ajinkya (2):
converting README to markdown format
moving HISTORY.txt to markdown format
Ajinkya Kale (49):
Refactoring math dir : deleting unused functions from discrete.cc
Refactoring math dir : deleting unused functions from discrete.h
Refactoring math dir : getting rid of unused kernels
Had removed factorial func by mistake which broke the build. Adding it back.
Had removed factorial func by mistake which broke the build. Adding it back.
Refactoring math dir : getting rid of unused functions
Refactoring math dir : getting rid of spherevolume function
Refactoring math dir : getting rid of spherevolume function
commit fcb59905c029ccf27d6ce1521259a712890f6a62
Refactoring math dir : getting rid of unused stuff
Refactoring math dir : removing discrete.cc, discrete.h, geometry.cc, geometry.h
Refactoring math dir : getting rid of unused functions and constants (#116: Investigate what is present and used in fastlib/math/)
Ticket #126 : PCA code
Ticket #126 : added entry for pca
added comments and made some formatting changes
changed the pca api. not using Armadillo's pca anymore. Still making a few changes ..need to check-in the comments to the api.
Code refactoring. Added comments to the methods.
<#126: Implement simple PCA> adding pca_test
<#126: Implement simple PCA> adding pca_test
<#126: Implement simple PCA> removing pca_test from pca dir (Added it in tests dir)
commit fcae3eb8368b36b295daa65824241dc42450401e
<#126: Implement simple PCA> changed assert to BOOST_REQUIRE_SMALL
<#165: PCA::Apply() fails with Armadillo error> was a minor bug in the indices passed to shed_cols
< #166: PCA fails comparison with MATLAB> centering and scaling was causing the difference. By default other packages do not do zero-centering and scaling with std deviation.
changed the test to accomodate pricipal axes in opp direction ie when eigenvectors returned are flipped in sign compared to the eignvec returned by matlab for the same dataset
changed the api to accomodate centering and scaling of initial dataset. There was a bug as the end result of the transformed data was not centered, the results were not matching those from matlab.
changed the api to accomodate centering and scaling of initial dataset.
and i present you <Kernel PCA>
got the implementation into hpp file to include it in the class def. This is need to make the templates work. Good article here which talk about why we need this http://www.comeaucomputing.com/techtalk/templates/#whylinkerror
commit b557d834d4dba5684c175b9d088895ddd981b917
kernel pca works with linear Kernel now.
commit 5f453206758a5f8682e152da58f748f3d9bb2898
kernel pca test file
exponential kernel
laplacian kernel
polynomial kernel
formatting changes
hyperbolic tangent kernel
fixed a few bugs
tests for the new kernels
commit 3dec62c0898d72027ba0316df76f2a6b20768ce5
added download link to build page on mlpack.org
adding index links
fixing mlpack homepage link
fixing headings
adding readme
fixing formatting
Update README.md
Update README.md
Barak A. Pearlmutter (16):
correct diferent spelling
upstream development repo moved from svn to git on github
merge upstream/2.0.0 carrying along only debian/*
forward port quilt patches, augment spelling patch
bump to libmlpack.so.2
build dependency on libboost-serialization-dev
upstream README.txt now README.md
remove obsolete field DM-Upload-Allowed
dh_install --list-missing
upstream now prefixes binaries with mlpack_
hdf5 include directory debian/rules tweak seems unnecessary
document html documentation
update debian/copyright per upstream COPYRIGHT.txt
canonicalize to lower case mlpack per upstream request
generated files to clean
log changes
Bill March (335):
Bill's code
Adding NSF proposal
Updated drafts
stuff
stuff
updated proposal
more draft
more NSF
nsf drafts
draft revisions
drafts again
drafts drafts drafts
I am sick of drafts
blah
added Union-Find data structure
updated emst
adding platonic allnn
cleaning up
updated comments
small updates
a few more changes
added some tests
last minute changes
cleaned it up
adding test data
deleted old file
minor changes
fixed UnionFind unit tests
hartree-fock code
unit tests for Ryan
changed stuff
code hooray
stuff
hf stuff
commit 36a1d0c2c0a1e66eb7a34e282c3504de88c91669
error testing stuff
changed stuff
fixed things
fixed lower bound problem
added readme
the build file helps
changing recursion to include square trees
fixed symmetry and hybrid error
scf working
fixed bug in DEBUG_APPROX_DOUBLE
working, but slow
more updates and fixes
I hate electrons.
before DIIS
hacky damping, woo
the hack works better
little cleanup
last minute
missing file
fixed Doxygen error in fx_submodule
fixed timers
fixed fx problems
Ryan can't spell, and cylces don't exist
made sure absolute prunes are impossible when lower bound is zero
quick fixes
added better multi-tree timing infrastructure
added another timer
some debug checks
added naive timing stuff
fixed mac error
quick typo fix
testing basis energies
commit 039896b87731c25f75e76c97b7c3a9f15f5de299
commit baab66f91f1149e4cdc544c838f2293c79dcb390
hf bound function
fixed optimization lib name
finding clusters with emst
commit ef0d9e5813207f4f8dbf303583c3a6dbb03eb963
commit a0bd03465970753e94f988c31a9039efa8c2b17e
Timing added.
MLPACK final demo version.
commit b75a9e2751ee505981dda72e0ec28726f2ae0f92
commit eaed08a6b8c1f52c1e9dcf7510643f898cf16bdd
commit 1b9f8882b874c10cd4adc93a3ae372153918dcd5
commit 228a9265774e22e5e308e0032806d41c0d13a4b4
commit ba86658b88f9bdb9d0220eca8662f2933e0fddd4
fixed build script for macs
commit 163e801eec2ed8a1df1ac0d48b1f104365ec1944
commit 2982edf6381d1419ff5b28f7e2d6372353f232cd
commit 4f0f22ee6bea1ccf682d85fd7dd2f8003c1040e6
commit 38f43cfaca9860200e37fe8ea3180620003fee6d
commit 81b66a87792356eeaac41e1d087ca94463c3498b
commit e5972ee6120f4200c3c231c4fe64ac2adb2347d1
commit fa9a48a995d9b278fd83e7a2553cc1beb1767cd9
commit a20ba322acf8fbe9a5d8563d461c242570b21216
commit b78f055d6cd14f94455181aeb5e5467461d14c72
commit fd8e34b6f79576614aba04da92128dbfbb298696
commit 79bd95b6ac34e1331315a45d8899256a4808088c
commit d1a321dcfc51571bf4676a1cd1e77808314d8ca4
commit 96b37c4b73497597a5b504dd712b077b387d525c
commit 8c301af76e94cedccb139f4d9dc70b6d537af99e
commit 31e6b0f057fee16fa1965347151f510d755f5a1d
commit 6c65bc6e3eeb6167aa658cc2f6ba6b86807fe4fb
commit 187031e79b6d131e8916bdbea4c7d12498b84f30
commit e1f9a779b659cef1e55a70fe5474518bd324e3b3
commit f818423d094eee7111380c5de25492bd51a52358
commit bad24bead6e01c215f1306bd924d60cb3649711e
commit 552145ee3e111b6b9ff1e232a35a437ce5b9c69f
commit 4f171d1225e4e2445293af407a9625beb950926b
rearranged directories
commit 2b268dec244f73fbacf7e2aba1611ba5b98e8742
changed output and added charges to base case
fixed symmetry in base case
commit 9f3fb2ad1a56a9759c46fcd8a0dd9c2b5ffcabf5
commit 635d5dac9eec89c285c8ecf9c8c362ce30fafad5
commit 548c1c43c4f93dde040b7cb81285979a454a711c
fixed uninitialized vector, worked on link and multi-tree
worked onlink sorting
copied approximation functions and updated bounds in multi tree code
finished copying functions over and added integral routines for distances
added some fx documentation
fixed exchange computation in naive and prescreening
fixed some overcouting in link, added sorting and merging of integral lists
fixed link integrals
put normalization inside integral code, added permutations
added docs
added weighted bounding box averaging
commit 032b154507ed5807a9cf1edcb8dc9d9c3632e700
added F_m
fixed cfmm base case
adding one electron integrals
added some one electron integrals and comparison code
fixed and standardized comparison against naive
fixed storage path for fxrun
commit 9284516181984415d32f52a6fe8a1f2a657159db
commit 68b4bf4f0e5315b17c5cd9c4ff2c8f1ab73b5afe
messed with schwartz factor
fixed num pruned shell pairs
fixed pointer bug
commit be9ca9cb28a6447fd8ce03883f9f672133b63849
fixed timing and docs in cfmm
commit 55a2df6968bf698c5ee2134c9f6a19e59b51ae3f
commit c10965433130de3fac0ef803d9ba32a78bc07877
fixed weighted average of bounding boxes
fixed bounds and error control in multi tree
fixed link sorting
fixed naive storage to work with fx-run
fixed naive storage to work with fx-run
storing integral components
commit 4ec026a18649abe30d8e45a0e70ef5a8ca011f42
commit 7a27f518b01a4bb24d51f6f929b59a1737cb4901
fixed oeints, started new verison of scf solver to replace old hf
adding schwartz bounds to multi-tree code
standardized fock algorithms for scf code. also added schwartz prescreening to multi tree
fixed scf integrals and compilation issues
changed mu_ind to lambda_ind
fixed link density check
everything but CFMM works with SCF code
updated scf output
cleaned up printing for scf code
fixed bug in core matrix computation
added core hamiltonian to comparison code
fixed nuclear charges reading
added ability to read density matrices from QChem
allowed cflags to be called by linker as well (added under Ryan's supervision)
added qchem density reading
fixed strcmp for qchem input
basic libint interface works
more improvements to integral code, fixed major problem with CanPrune_()
fixed remaining_epsilon in PropagateBoundsUp_()
commit 43bbf318fcb26bbab5cce683768510f8e14e9a2f
commit de675f043e63a22715264ce8f4b72d1fc76659ad
commit 0a519ebcdec4af3e1674344bdfaf0c7371fc9a39
tried fixing remaining references in FillApproximationCoulomb_
tried more error fixes, worked on normalizing integrals, fixed reinitialization of matrices in comparison code
fixed permutation error for density matrices, added normalization to integral wrappers
updated exchange error
few book-keeping fixes
changed to prescreening comparison for error
tried to reduce memory usage of multi tree
added ability to compute combined CFMM/LinK energies
fixed memory usage in CFMM/LinK comparison
removed matrix saving
fixed multi output
added storage of overlap and core matrices in comparison code
added storage of overlap and core matrices in comparison code
added documentation for nuclear centers
added documentation for nuclear centers
fixed exit failure for multi tree runs
changed eri code over to higher momenta
Created IntegralTensor class to handle unpermuting integrals
fixed auxiliary integral calculation and added ssss integral support
added higher momentum overlap integral and some test code
added kinetic and nuclear integrals
working on higher momentum SCF code
fixed kinetic integrals
energies correct for single atoms
working on F_m
added other F_m computations
finished prescreening, started on link
link working
updated CFMM
updated CFMM to handle higher momenta
wrote BasisShell tree, working on testing it
shell tree tests working
added matrix tree
wrote matrix tree tests
base case and tree construction working
implemented absolute error pruning and bounds infrastructure
added and tested bounds, fixed node counts
more updates to work with higher momentum code
changed build file to work on either machine
trying to fix memory errors
trying to fix memory errors
fixed memory leak error
fixed splitting of off-diagonal matrix tree nodes
cleaned up for testing
fixed memory leaks
split coulomb and exchange recursion, added prescreening prune
fixed memory leak
fixed memory leak #2
EMST on cover tree
implemented cover tree emst
hybrid expansion pattern
bug fixing
adding comparison code
added sorting of edges
debugging
debugged
cleanup, added documentation
added sorting and documentation
wrote GeoMST
cleaned up output for experiments
added the single fragment algorithm from Friedman & Bentley's 1977 paper
wrote NEKMA multi-fragment algorithm
fixed bug in nearest neighbor finder, corrected multi-fragment algorithm
fixed multi fragment bug
fixed bug in cover tree version, needed to ensure valid bound in CopyCoverSets_
added new prunes to cover tree: setting upper bound for ref in base case and implied bound in ref descend
fixed error in implied prune, must have d(q, r) large
n-point correlations, wrote basic kernel function
wrote base case and naive code to use it, few more problems with passing partial tuples around, tests to come
and now, to actually add the files
fixed a few small errors, made test cases, naive works for 2 and 3 point tests
wrote depth first recursive code, fixed bug in base case
wrote and tested counting function
wrote basic hybrid expansion pattern, wrote function to test node lists
finished hybrid expansion, added bad symmetry output to node checks
fixed bug in hybrid expansion - can't exit checking a node tuple when a pair excludes because the tuple may still have bad symmetry
actually fixed it now, replaced decrementing a global lower bound with just summing up the bounds as I traverse the new list.
working on multi-bandwidth version
wrote permutation free version
updated cmake list
Permutation free version works for just upper bounds as long as I recompute all the distances after each split. Need to work on UpdateIndices_() to figure out why keeping them doesn't work. Add lower bounds after that.
fixed bug in UpdateIndices_, was using wrong index
added lower bounds to perm-free, stopped recomputing invalid indices
wrote multi-matcher with inefficient base case
base case & output debugged, on to pruning
successfully debugged for small 2 and 3 point tests
improved pruning slightly
fixed a memory leak when copying arrays of GenMatrices
fixed memory leak, should be fine now
wrote code to time single matcher code over multiple matchers
fixed small error in naive multi main
reorganizing HF code
added boost 1.45.0 to Boost_ADDITIONAL_VERSIONS
fixed casting error in fastica, changed isnan and isinf to std:isnan, std::isinf in kde
started new implementaion of n-point, wrote Permutations and tested it
wrote and tested single matcher
wrote old auton-style multi-tree n-point, did very basic tests, needs more testing.
wrote naive npt
fixed bug in naive code, wrote I/O for main, started on permutation-free algorithm.
writing body of matcher and node_tuple
finished writing permutation free version
finished perm free alg, fixing bugs
fixed bugs in perm free implementation, now naive, single, and perm free are correct on 2 and 3pt tests
I lied before, but now perm free is actually fixed and passes 3pt tests
added timing stuff to n_point_main
fixed a pruning error, wasn't catching bad symmetry cases
added multi bandwidth to main
rewrote perm_free node list updates, starting on multi bandwidth reimplementation
wrote generic multi bandwidth code, still a few bugs, though
added better output, fixed bug in indexing
fixed bugs in the multi bandwidth version, writing new I/O
making the constructors uniform
Added matcher generator, passes basic tests
made sure that multi bandwidth computed results for the upper limit of the input as well
updated single bandwidth main
removed deprecated fx stuff
fixed PARAM info
added PARAM_FLAG() etc. to multi bandwidth main
fixed PARAM stuff
added support for DDR-type counts
started implementation of specialized case, wrote most of algorithm class, wrote point tuple comparison for matcher
finished up angle implementation
added support to for single matcher alg to angle matcher main, fixing bugs
crusing bugs (and it helps to call Compute())
trying new angle-based pruning rule
fixed bug in angle pruning
fixed tree stuff and corrected angle based pruning
cleaned up angle code
reorganized code to take generic algorithm class, results are now stored in the matchers, which probably need to be renamed
working on weird tree bug
right CMakeList
right CMakeList
finished up generic angle version, still not sure what was wrong with the nodes for a while
added resampling code
wrapping up resampling code
cleared out npt, moving current stuff over for major refactoring
added CMakeLists.txt, apparently not having one breaks the build?
the refactoring continues
more refactoring
refactoring continues
wrapping up refactoring
adding single computation main for verification
added single matcher test infrastructure
wrote simple, serial two_point_correlation code; currently only does DD and DR counts (and not at the same time)
distributed two point implementation
added two point tests
single_main change
fixed two_point test, reading a float from file isn't the same as the original float
fixing tests, writing distributed test
working on distributed two point
added full sized tests and different num_threads, everything still passes
committing small changes in advance of destruction
fixed a comment, added paper citation
wrote very basic two point kernel and tests
updated n_point for reorganized mlpack, also removed link against fastlib in contrib/CMakeLists.txt
adding (nonworking) single bandwidth test, removed fastlib from contrib's CMakeLists.txt
added angle resampling tests, squished some bugs, still a few to go.
sorry, broke the build; I'm now completely in favor of Ryan's idea to move contrib out of the mlpack directory.
refactored random generation stuff, wrote a simple timing case
fixed small bug in angle results, made random generation stuff backwards compatible with boost (hopefully)
wrote emst_tests, fixed a few problems created by blindly replacing index_t with size_t
cleaned up a bit
split dtb into _impl.hpp, should finish off ticket 117
fixed compilation error for boost 1.47 by adding <> to uniform_01
fixed line that referred to nearest neighbor search
wrote EMST tutorial
Updated EMST code to use tree traverser abstractions.
Dongryeol Lee (2664):
hi
moved over Auton KDE distribution here, but it has to be ported. I'll do this later
Initial checkin of the series expansion stuff in a library form
Update to the series expansion library
More unit test for series expansion
Partially templatized series expansion class, still need to implement for Epanechnikov Kernel
Cleanup in progress for expansion stuff
Made SeriesExpansionAux object with SeriesExpansion class as a pointer
Added BinomialCoefficient method under discrete.cc/discrete.h
Small bug fix in TransFarToFar: the order of the approximation was set to 0, but it really should have been set to the order of the translated expansion
Added a new member variable under SeriesExpansionAux for speeding up convolution sum
Added acceleration for TransFarToFar operator
Added acceleration for TransLocalToLocal
Added the method for computing the required order of approximation for H2L operator
Initial checkin of derivative computer
Templatized kernel derivative computer
Added in derivative computation for Epanechnikov kernel, but needs to be tested
Now supports Epanechinkov transform using the generalized FMM framework. Need to workout some cancellation error issue
Some fixes for cancellation error that might pop up for complex cases
Going to break up SeriesExpansion class into FarFieldExpansion and LocalExpansion classes (objectifying)
Added LocalExpansion class (to be ported over from SeriesExpansion class)
Objectification complete, need to fill out error bound functions
Epanechinkov expansion bug finally caught
Removed series_expansion.h since it was split into FarFieldExpansion and LocalExpansion
Ported over error bound computation for Gaussian expansions
commit 99259a902cf145682a3a0f59550906deac748cfa
Initial checkin of multibody code
Porting in progress, added in basic skeleton of the code
Added the basic finite difference scheme, now debugging and unit testing remains
Exhaustive multibody coded in for three-body Gaussian
multibody porting completed, now have to add in expansion stuff
Pruning rule with error reclamation
more code restructuring, with MultibodyKernel defined
more code restructuring, with MultibodyKernel defined
more code cleanup
Basic form of 3-way convolution added for series expansion
Convolution form of three-body summation added, but needs debugging
All bugs fixed for three-way convolution
Test case added for Three way convolution of Gaussian sums
Added in three-way convolution for Gaussian in multibody code
More compilation fixes, still need to add in error bound computation for convolution and more fancier approximation methods
some minor changes, regarding generalization beyond 3-body
More memory bug fix for seriesexpansion class
final bug fix on three-way convolution - fixed the bug that made the centroid of each node as zero vector
Added in combination enumerator, now ready to transition to hybrid algorithm
Initial check in of LHC stuff
restructuring
main driver added
Now compilable, still need to port the rest
Fully ported tree-based orthogonal range search
All bugs fixed for single-tree orthogonal range queries
Starting implementation of dual-tree based orthogonal range queries
Now the timing comparison between the two is fair
restructuring for batch experiment
Added combination to rank function
Version before adding in bidirectional optimization
Now records speedup factor over naive
Initial version of bidirectional, needs improvement
still needs improvement
Implemented a second cheaper convolution of two multipole moments mixed in with exhaustive computation
Tried out both types of series expansion, but does not work, will be focusing on bidirectional version
Another version
Bug fix
Checkin before the porting
started kde header file
Axilrod-Teller ported
Started series expansion based KDE class
Added naive KDE
Basic skeleton of KDE ported
Added proximity project directory, now starting on FFT version of KDE
Spill kd-tree implemented
Added main.cc
basic finite difference KDE ported, now need to plug in series expansion
Finite difference debugged
mean shift directory added, enhanced pruning rule for kde in effect
Basic skeleton of series expansion stuff added, but needs to add in the core part
Took debugging part
Single bandwidth KDE with series-based acceleration has been ported
PCA tree in progress
started fft version of KDE
Ported more of fft KDE
Miscellaenous cleanup
FFT KDE compiles now, now need to debug
Combined error bound computation and derivative computations into a single class
now supports KDE with Epanechnikov kernel series-expansion
Initial directory checkin of local polynomial regression
a small bug fix for far field evaluation - the function really needed to take the approximation order but it evaluated up to the full order
p^D expansion stuff
updated the build file for the series expansion library
small bug fix on multiplicative kernel expansion
another bug fix
more bug fix on translation operators for multiplicative kernel
generalized plug-in series-expansion framework completed
needs fixing for fft KDE
FFT KDE fully debugged.
Started LPR
Naive local polynomial regression completed
Small fix for checking against exhaustive result
Fixed so that scaling is done before the tree construction
some adjustment in p^D expansion
FGT KDE being ported
Change to multibody code due to SeriesExpansion library change
Simplified error bound for D^p expansion
FGT KDE debugged
some minor changes in timing for FGT KDE
Initial commit for experimental setup of IFGT
DataAdaptive IFGT bug fix
Experimental setup fix for IFGT
Some bug fixes for KDE
memory bug has been fixed
currently tweaked KDE for p^D expansion for experiments
compilation fix for multibody
small fix in the upper bound change computation in Prunable
another fix for UpdateBounds
restructuring of the build file
modified post processing function to fully update lower and upper bounds for each query point
Redefined function sets for SeriesExpansion classes, and fixed compilation errors due to this change
hierarhicical pca almost completed
hierarchical pca debugging
hierarchical pca fixed!
pca tree final commit
generalized kd-tree with plug-in split rules
checkin of thor kde (initial)
skeleton thor KDE compiles, but needs to fill in function
adding skeleton thor KDE
marched through the initialization and tree construction phase of thor
minor change to series expansion
Thor KDE does not crash any more, but stub functions need to be filled in
Filled out a portion of the skeleton of THOR KDE
finite difference KDE without optimization written, debugging left
checkin of what i have now
THOR KDE with pure finite difference works
all bugs in thor kde finite difference ironed out, need to add in further optimizations
Added Garry's optimized pruning rule, just need to integrate series expansion stuffs now
quick fix on the timer stuff for timing naive
cleaned up the template mess in series expansion class and fixed compilation errors due to the template cleanup
new formulation of KDE using THOR semantic
Converted KDE to use THOR grammar
Made separate mains for fgt and fft
THOR-style DFS series-expansion based KDE implemented
Small compilation change in multiplicative expansion
critical performance bug fix
factorial functions in auxilary series expansion object converted to const functions
Does cutoff of singular value based on its value compared to the maximum
Fix on generalized kd-tree implementation
added two options for expansion pattern for THOR-based KDE
Separated naive kde implementation into separate file
tree saving/loading supported
currently saves the permuted matrix dataset, but need to figure out how apply permutation
range search with serialization finished
quick fix to account for dataset permutation
Compilation fixes before the code freeze
Took out the parts that are currently under development
Swapped the thor-style KDE with the current stable version
old version of KDE is bugged, so I'm checking in the thor-style KDE which works
Took out dataset reading from algorithm core
Added dataset scaler
Renamed main.cc to kde_main.cc
Fast KDE is now using submodule for organizing parameters
Extensive commenting and instructions on how to run fast kde is completed
FFT based KDE fully documented
Basic documentation for running FGT based KDE completed
Bug fix in FGT based KDE
General commenting updates
more doxygen stuff
removed thor style KDE (backup version)
Another pass in doxygen-style documentations
Checking in more documented stuffs
Added the original IFGT, took out the bugged IFGT
Minor commenting correction
Renamed the main driver file
Fixed up user-level functions for better interfacing
Another quick fix under debug mode
More extensive commenting on the FGT code
Added automatic parameter tuning for the original IFGT
Minor print statement taken out from IFGT
Finished doxygen-style commenting
Minor doxygen comment fix
Minor doxygen comment correction
A fix for OrthoRangeSearch objects to support multiple usages for a single object
Initial checkin of the multibody code
declared OrthoRangeSearch class to be non-copiable
Minor documentation changes
Added the original vanilla dual-tree KDE
Added error reclamation trick for the dualtree KDE
memory consumption fix
Added the vanilla dual-tree KDE
Initial checkin of the regression package to be released
Outlined the basic form of the algorithm
Implementation header initial checkin
Changed the build file
Base case of the phase 1 algorithm flashed out
Skeleton 4-way recursion code added in
Finished the pruning rule
Added preprocessing for the reference tree
Some file renaming, added the header for post processing
Finished the postprocessing for the first phase of the algorithm
Restructuring of the files
Changed the field variable names of Stat class to be more general
Basically ready to start the Krylov phase of the algorithm
more structuring
More initialization routines completed
Ready to start the skeleton dual-tree code for the 2nd phase
Base case for the second phase completed...
Finished the rough structure except for the main Krylov subspace solver
Fixed the postprocessing function for the 2nd phase
SYMMLQ function finished. Debuggin in process
Currently debugging
Middle of debugging
Phase 1 debugged
Added the test file for phase 1
The first working version of the matrix-free Krylov subspace local linear regression
Completely debugged locally linear regression
Changed the scaling
Added a new scaling function
Added the naive method
Fixed the local linear naive code
Fixed the local linear naive code
Fixed a crucial bug in naive local linear
Fixed a small performance bug
Need to replace SYMMLQ method with Lanczos tridiagonalizer
Now phase 2 does relative error
Took out the test routine
Performance enhancement
Krylov subspace version of local linear regression completed
Renamed the naive algorithm to handle locally constant regression
initial check in of the dense version of local polynomial regression
Restructuring the utility class
Added the implementation file for the dense version of LPR
Added utility class for matrix
Base case finished
Finished the query tree initialization phase for dense version of LPR
Algorithm reformulation
More fixes
Finished implementing the dense formulation of LPR
Fixed the compilation error
Fixed the compilation error
Debuggin in process
More fixes
Bug fix
Fixed the compilation error
More fix
Fix for NWR
Bug fix in naive local polynomial
Minor fix to dense LPR code
Another fix to the naive lpr code
Fix in the matrix util
Minor fixes to output module
Added Deng and Moore's pruning rule, but needs to be filled in
More utility functions for testing correctness
Confirmed the correctness of the pruning
Fixed parameter module
Fixing the naive algorithm to compute confidence bands
Naive algorithm now outputs confidence bands
Verified the naive algorithm
Took out the template argument that specified the local polynomial order
Variable bandwidth for naive algorithm implemented
Minior fix to the do LOO nn search
Naive LPR confidence band fix
Minor addition to the driver file
Modified the tree-based code to do train/prediction phase separately
Little fix on the parameter
Need to fix the correctness of dense LPR
Some bug fix
No bug - just a misuse of the kernel function in two algorithms during comparison
Fast code now computes confidence bands
Epanechnikov series expansion added for code
Minor variable name fix
Some performance tuning
Added the lower bound optimization for the dense formulation
Dense LPR cannot run beyond linear order
Change in bound computing function
Faster Epanechnikov pruning added
Now does proper pruning based on the B^T W(q)^2 B component, with Epanechnikov kernel acceleration
Final performance tuning on the dense version of the algorithm
Added variable bandwidth support
Methods added to the main driver
Single tree mode added
Naive algorithm now uses much less memory
Some compiling error fix for the matrix-free driver
Took out EpanKernel moment out and made it a separate header
Renamed and restructured the matrix-free version
Second round of going through and fixing compilation errors
Almost done reviving the matrix-free version of LPR
Minor bug fix
A minor fix
Fix in the bug in pruning
Went through up to the phase 1 part of the matrix free algorithm
Started debugging the krylov solver part
Added a utility function for LPR
Separated out heuristic function for node expansion into a separate file
More fix to come for krylov_lpr_solver_impl.h
Got it to compile
Last generation of the bugs have been caught for krylov LPR
More crashes caught
Bug in Phase 2 detected. need to fix now
Phase 1 has Epanechnikov acceleration added
Last attempt on krylov-based method
Epanechnikov acceleration added to Krylov method
Sparse version now stores dense far-field moments
Finally done with matrix-free version
Memory consumption cut in half
Need to fix matrix-free version now
Fix for variable bandwidth
Initial check in of dense version
Added the naive version
Added the multiindex expansion tool
Fixed the bug on the knn bandwidth
Fix to the variable bandwidth case
Removed the custom-built Krylov solver, now going to replace it with Epetra solver
Got Epetra stuff to compile
Compiled the iterative method... Now debugging
Still does not work - possibly misuse or a bug in AztecOO
Everything is fixed, and it works now
A bug in the matrix-vector multiplier. Need to fix now
There was a problem in reference-side initialization - needed to clear out the Epanechnikov moments, but didn't. Now the reference stats are reset everytime the dual-tree multiplier call is made
Initial check in of the Multi Conjugate-Gradient algorithm
Some more tweaks
A minor bug fix in CG method - needed to subtract off the number of queries at one point
Added the optimization for letting converged queries exit the Krylov loop.
Added the Krylov solver file
Added a solver file to the build file description
Fix in the parameter retrieval in the matrix-free method
Edited the status message a bit in the CG loop
Need to optimize more by sharing stratification results
Optimized the performance of the CG-based LPR algorithm
Now saves the first column of the linear operators for the matrix-free version, but this is still linear in the number of unknowns
Revived the proximity project under new CVS
Added the ball-tree
A little optimization in the stratified computation, but did not help much - going to save distance computations as well
Added Modified Gram Schmidt and batch point mutivariate expansion utilities
One bug in multi-cg loop caught - needed to maintain separate r dot z (old) values, but the previous one shared a global one
Added a utility for computing the coordinate of the point that is farthest away from a given point inside a given bounding ball
Added the leave-one-out regression estimates for the reference set training stage
Now precomputes query point expansions before finalizing regression estimates, since they are needed in computing the confidence intervals (need to be passed to the Krylov solver). The Krylov solver needs to be modified, plus one final dual-tree pass over the computed solution vectors need to be implemented
Fixed the compilation error for general kd-tree code
Now computes the influence values for each reference point, need to add in the final dual-tree pass for computing the magnitude of each weight diagram vector for each reference point to construct the confidence interval
Fixed a bug in the dense version of the algorithm which did not shuffle the computed magnitude of weight diagrams and influence values accordingly due to the query tree construction; also there was a logic mistake in the design of the code which assumed that under variable-bandwidth case, the epanechnikov moment computed for the denominator matrix could be used for the weight diagram matrix, but this is not true since the effective normalization constant for weight diagram matrix re [...]
Caught a serious bug in non-shuffling of the weight diagram magnitude and influence values in the dense version of the algorithm
Now shuffles the values for weight diagram and influence values for Krylov version
Fix in the compute function for naive code which contained erroneous extra argument
Fix in the compute function for naive code which contained erroneous extra argument
Krylov subspace based LPR now computes full information required for crossvalidation: confidence bands, regression estimate, leave-one-out regression estimate, influence value, and magnitude of its weight diagram vector in the hat matrix
Some work for setting up the experiment for the dense version of the algorithm has been completed. I now need to look at the krylov subspace version for correctness since I do some fancy stuff for the normalization constants
Minor fixes in the user-level function Compute
The naive code had a bug in computing the influence value of a point; it should have computed t(q)^T (B^T W(q) B)^{-1} t(q) W(0), instead of t(q)^T (B^T W(q) B)^{-1} t(q)
Bug fix in the dense version: same problem with the naive version since I forgot to divided by the normalization constant for the influence values
Last generation of the Krylov subspace based method has been caught - the bug was due to reusing the same dual-tree computation function across three different phases (some phases were required to use squared kernel values, rather than the regular values)
Another fix to the Compute function
Tweaked the termination condition in the CG algorithm
Edited the krylov-based regression code for numerical stability
I need to fix the Krylov loop to make sure all three system solutions have converged before a query exists the Krylov loop.
Fixed the normalization constant handling for query influence values
More parameter tweaking in the CG loop
indentation fix in multi_conjugate_gradient.h
Bug fix in the Krylov loop - changed a break statement in the for-loop that iterated over each query to a continue statement
More fixes in CG loop regarding the updating the solutions
Numerical stability fix
Separated out the naive algorithm into a separate file. Now algorithms are templatized for different primitive types
Fastlib tree now is OT-compliant, meaning it can be serialized/unserialized. However, it still does not admit a bounding box of general primitive type (for example, a short-int based bounding box rather than a double-based bounding box), which would involve making changes to bounds.h, math/math.h:DRange class.
The driver application now reads in a dataset of short ints for demonstration.
Fixed the compilation error
Metric tree had a bug, and now it is fixed...
Adding general typed ranges.
Separated the global variable declarations into a separate cc file
Separated the global variable declarations into a separate cc file
Now uses static allocation for matrices (Nick's memory manager)
Added Static versions of the Init/Own/Copy function that allocates using Nick's memory mapped files.
Minor editing of the build file
Added Static Init function for the general bound type.
Added a directory for testing variants of PCA
Renamed the class name to make it a static class supporting different modes of PCA computation.
Compilation error fix.
More compilation fix. Now starting the fix-point algorithm.
Completed the fixed-point algorithm for PCA
Fix to the pruning rule in dualtree_kde.h
Fixed a potential performance bug in the KDE code that resulted in a stricter pruning criterion.
Now uses median split KD-tree
Fixed a bug in median split kd-tree that resulted in infinite recursion.
Still need to fix the stitching problem in pca_tree.h
Updated a potential bug in the ball tree that could attempt to split even if the radius is very close to zero. Changed DBL_MIN to DBL_EPSILON as a result.
SVD Tree has numerical stability issue when applied to high-dimensional matrices. Going to fix this using orthogonal iteration.
Fixed the SeriesExpansion module so that it is up to date with the current library. Changed const ArrayList to const ArrayList references.
Minor change to the dualtree_kde.h to use InitCopy instead of Copy, a deprecated function.
Renamed pca_tree.h to subspace_stat.h. This file will be templatized for different ways of stitching up two different subspaces.
Fixed the compilation errors. Plus added the module to compute principal angles between two subspaces.
Needs to be debugged.
Memory leak error for ball-tree has been fixed...
Added the function for making kdtrees out of hyperrectangles.
Compilation error fix
Added splitting functions for making trees out of hyperrectangles.
Fixed the tree constructor for hyperrectangles.
Orthogonal range code now supports multiple orthogonal range queries. Need to be debugged.
Fixed memory leak error
Fixed a bug in partitioning function for constructing trees out of hyperrectnalges.
A little change to the main test driver for range search code.
Debugging is done... Now need to optimize...
Restarted the hierarchical pca algorithm, now replaced with Vempala's fast SVD algorithm. Need to finish the subspace combining part...
Replaced EigenvectorsInit call which did not return eigenvalues in sorted order with SVDInit call which does.
Completed the base fast SVD case for which the number of points is less than the dimension...
Finished the base case, now have to work on the merging phase...
Replaced unstable SVD merging step with regular Monte Carlo algorithm. Now going to try out a possibly more stable approach.
Finished the hierarchical PCA algorithm. Now need to work on high dimensional FMM.
Eliminated the storage space for the right singular vectors.
Modified dataset scaler to avoid division by zero.
Added the function for computing maximum l2 norm reconstructoin error
Loop fusion on Accumulate function mult_local_expansion.h
Implemented the core functions estimating the computational cost for evaluating a far field expansion, far-to-local translation operator, and direct local accumulation.
Now the code uses the implemented cost functions in series expansion library.
More fixes to const reference problems for ArrayList
Added some skeletons for Monte Carlo evaluation and prototypes for doing in O(D^p) expansion.
Fixed the ball-tree to be compatible with the fastlib tree interface, fixed subspace_stat class to have the correct mean vector in the case of the node owning only one point.
Templatized the series expansion to accept arbitrary bound types.
Added the cut-off criterion for pre-determining how many order of coefficients to precompute.
Separated the far-field expansion into an implementation file to shorten the file lengths.
Separated out the implementations of series expansion into separate impl files
Fixed the build file so that it compiles.
Added the linear-time CUR decomposition algorithm.
Bug fix in CUR decomposition computation.
Added matrix factorization formulation of far-field and local expansions.
Took out Monte Carlo evaluation for D^p expansion. Fixed a bug in CUR decomposition that caused NaNs for matrices close to zero matrix.
Changed the prototype for the training function for the kernel-independent fmm
Edited the CUR decomposition such that it returns the decomposition with sorted column numbers and row numbers.
Finished the far-field moment computation for the kernel-independent fmm
Bug fix in the CUR decomposition that did not initialize the R matrix in the right size. Implemented the far-to-far translation operator for the matrix factorization FMM.
Added the far-field to local translation operator for the matrix factorization fmm
Added the local-to-local translation operator.
Added the basis training for the local expansion of the leaf nodes.
Initial checkin of the matrix factorized version of FMM.
Moved matrix-factorization FMM test implementation to contrib directory.
Initial checkin of the matrix-factorized FMM
Added the empty driver for the matrix factorized FMM.
Fixed the compilation error.
Added the wrapper kernel class for the matrix-factorized FMM.
More compilation error fix.
More compilation error fix.
Forgot to initialize the local moments - now wrote the code for doing so.
Implemented the evaluation method for matrix-factorized local expansion.
Need to implement the canonical dual-tree recursion and debug...
It works sort of - I need to figure out how to do automatic error control at least probabilistically.
Some minor fixes to the matrix factorized series expansion.
Updated the matrix-factorized fmm to use exact cur decomposition with pivotting qr.
A minor fix to the matrix-factorized FMM. Still need to figure out how to do error bounds.
A segmentation fault fix.
Reverted back to the old CUR version... Now need to debug...
Bug fix in forming the outgoing representation - incorrect matrix-vector multiplication has been fixed.
A little tweak in the number of samples to take in CUR decomposition - this needs to be automated!
A minor change to the code that involves how to compute the ending index of the points owned by the node.
Works reasonable well - now need to enforce that the local moments are actually pushed downwards whenever the query tree is recursed so that we get a tighter lower bound.
Minor bug fix plus now the far-field expansion of the matrix-factorized version stores the maximum incurred error in approximation.
Fixed the bug that caused FurthestColumnIndex column to return -1 as the index.
Current stable version.
Some tweaking in the number of row/column samples taken in CUR decomposition.
Documentation stuff added for the dual-tree based KDE code.
Added the code for standardizing the dataset.
Initial check in of the Monte Carlo version of FMM.
Finished prototype. Now need to optimize.
Reasonably behaves well - now need to put in probability recycling mechanism.
Added probability recycling mechanism.
Bug fix in probability reclaiming trick.
Now the code does finite-difference pruning for hard-to-sample cases.
Parameter tweaking to achieve more speedup.
Additional parameter tweaking for performance enhancement.
Additional parameter tweaking for performance enhancement.
Separated the dualtree implementation of KDE into separate files.
Removed the THOR-style KDE.
Added Monte Carlo style pruning.
Fixed the Monte Carlo sampling to be per-query basis.
Tweaked the performace by handling the probability redistribution in a smarter way.
Bug fix.
Fixed the probability allocation phase not to do so when the exact answers are required (p = 1)
Incorporated probability recycling mechanism.
Bug fix for not clearing out postponed extra probability in the base case.
Another bug fix in BestNodePartners_ which sometimes made nonsensical probability distribution (over 100 %)
Latest stable version - need to put in PCA tree trick.
More performance tweak in Monte Carlo sampling.
The current stable version without PCA tree trick.
Squared error optimization for Monte Carlo FMM series expansion.
Bug fix on using series expansion with probabilistic error bound.
Corrected the code to be const correct.
Bandwidth cross-validation by least squares criterion added.
Removed an initial implementation of Monte Carlo FMM since it has been integrated to the main KDE code.
Added the demonstration of Chebyshev economization in Mathematica code.
Renamed the main driver file name
Added the force vector derivation for Axilrod-Teller potential.
Added and corrected stuff on latex writeup.
Code upgrade to compute force vectors due to Axilrod-Teller potential in progress.
Removed a bidirectional version of multibody.
Debugged up to base case computation.
The code compiles, but long hours of debugging to come.
Finished coding simple finite difference version. Monte Carlo version forth-coming and debugging to be initiated.
Naive Axilrod-Teller force vector computation added.
Not much pruning happening. Debugging in progress.
Debuggin in progress. Now prunes a little bit, but slower than naive.
Added the new directory to start a new version of local polynomial regression using batch SVD
Added two more files - driver and the user level function implementation.
Removed local polynomial regression using SVD factorization, since it might not be a good idea to store dense factorizations for all points. Going back to the Krylov subspace method idea.
Some bug fix.
More bug fix - Eval function for 3 three nodes should have computed node-bound distances before concluding that the min distance was zero.
Fully debugged up to force computation, now need to incorporate Monte Carlo pruning.
A quick bug fix that overestimated the number of (n - 1) tuples.
In progress to use Monte Carlo pruning.
Modularized the Axilrod Teller kernel code (multibody_kernel.h). Now need to finish Monte Carlo scheme.
Finished Monte Carlo version. Now need to carefully go through and verify the code...
Kind of working. Need to go through and verify the code.
A little bug fix and changed lower/upper bounds to use Monte Carlo estimate and to influence the contribution estimation.
A major overhaul on the Monte Carlo sampling for KDE algorithm. Now uses sample variance for the pruning rule and does it in a true dual-tree fashion.
Fixed a critical bug that did not push down estimated mass in the Monte Carlo case.
Minor comestic repair in the comments.
Another minor cosmetic surgery in the comments.
Another minor cosmetic change.
revert back to using the central-limit theorem-based Monte Carlo approximation. Putting confidence band on extreme order statistics is not a practical idea.
Need to think about optimizing the right hand side of the pruning rule, not the left-hand side. Minor fixes checked in.
Bug fix for math::BinomialCoefficient(n, k); the previous implementation returned 1 for negative k values, which is not correct (should be zero.
Incorporated the rudimentary probability recycling scheme.
Incorporated the rudimentary probability recycling scheme.
Separated the statistics class object from DualtreeKde class for shortening the file length.
Corrected the writeup derivation.
Critical bug-fix in Monte Carlo sampling code. Now need to confirm that the rank order statistics is a good idea.
Error reclaiming implemented.
Fixed the Monte Carlo approximation.
A little tweak for probability reclaiming.
Added in the coverage percentile as a tweak parameter.
Added nonuniform nonnegative weight support.
Added the routine for outputting a LSCV score for a particular bandwidth.
Fixed the probability computation to do one-sided computation.
Now outputs the query estimate to the file.
New Monte Carlo scheme implemented.
Initial checkin of the variable-bandwidth KDE stubs. To be completed very soon.
Variable bandwidth KDE implemented. Need to look over to see whether it is working correctly or not.
Bug fix in variable-bandwidth KDE, where the preprocessing function had a overflow problem.
Added the naive computation of variable bandwidth KDE.
Fixed the double-initialization in variable KDE (kernels_ object).
A little tweak in the variable KDE Monte Carlo pruning scheme. Now need to re-factor out the common code between the fixed bandwidth and the variable-bandwidth code.
Compliation error fix.
A little tweak in the way Monte Carlo sampling is done - now tries to the maximize the lower kernel value to encourage more pruning.
Now the bound refinement algorithm takes the (1 - \alpha)-th statistics instead of the absolute minimum.
Made a permanent private temporary vector for sorting, instead of allocating everytime.
Added the leave-one-out feature.
Alphabetized the parameter list.
Fixed the initialization problem for the case when the reference did not equal the query.
Some fixes to the pruning rule.
Before adding in the bound refinement optimization.
Bug fix: did not reset the bound statistics for used error in the base case.
Current version with all optimizations added in.
Bug fix: a real solution is to have different stats for the query/reference tree, but this should fix now.
More optimization.
Alternative Monte Carlo scheme added back in.
Now dumps the relative error of each estimate to the file.
Added the brand new directory for the final public release of local polynomial regression code.
Removed some files.
Taking out core common functions in variable bandwidth/fixed bandwidth code.
Some more re-factorizing common parts.
Decrease in 42 lines of code.
Eliminated over 100 lines of code.
Reduced 140 lines of code by refactoring.
Latest change commited.
Vanilla finite-difference LSCV bandwidth cross-validator added. This one is definitely faster than the old algorithm.
Bug fix in dualtree_kde_cv.h
Added the missing file.
Bug fix in computing the plugin bandwidth.
Bug fix in LSCV score computation.
Compilation error fixed.
Code refactorization.
Added in Monte Carlo approximation.
Removed the matrix-factorized FMM modules since they are in beta stages.
Removed references to Monte Carlo.
Added the convolution operation for doubly nested kernel sums.
Series-expansion completed for kernel CV code.
Bug fixes in prunable function. Need to go through again to make sure variable names are mixed in accidentally.
General performance tune up.
Code cleanup.
Added the modules for doing spherical harmonic expansion for inverse power distance functions, but they need to be completed!
Some more addition to spherical harmonic expansion.
Multipole moments are computed correctly as of now.
Added the local expansion for inverse power distance kernels.
Evaluating the far-field expansion of inverse distance kernels sort of works.
Bug totally fixed on far-field evaluation. Now moving onto local field formation.
I have debugged up to farfield/local expansion formation and evaluation. Now need to implement the translation operators.
For backup purposes, I have moved the experimental series expansion using matrix factorized formulation here.
Implemented the far-field to local translation.
Coded up to F2F, and F2L operators. Now need to finish L2L operator.
Some bug fixes, but I need to go through these carefully.
Caught more bugs, I think I need to go through and check whether each constants are precomputed correctly.
I think the far-to-local translation finally works!
I think local-to-local translation works now, but I need to double-check.
Need to reconfirm that it is working correctly.
With 99.9% confidence, I think the inverse distance kernel expansions are working correctly. Now need to implement oct-tree.
Added the generalized oct-tree for higher-dimensional case.
Minor bug fix in octree.
Fixed the node ordering to resemble something like Z-ordering. Now performs Z-ordering per level, and stores the node list level-wise.
Bit interleaving/deinterleaving stuffs added for fast neighboring node finding for octree.
Initial checkin of the FMM implementation.
Now builds the octree, but need to confirm that it is being built correctly.
Templatized the octree to use arbitrary stat types.
Change due to templatization of octree.
Changed the octree code to take multiple point sets.
Code change due to octree change.
Upward pass phase completed.
Prevents dividing into infinitesimal boxes by putting DBL_EPSILON limit in the code.
Added the print function for octree
Octree has been changed: I think there was a bug in adding each newly created node to the node list. It was added to the level above than it should be.
Fixed another bug that did not index the points owned by each node properly.
Separated out the utility functions for octree.
More crucial bug fix in octree.
Added the function for computing another interaction list for octree.
Kind of finished, but need to go through the code and debug.
Checked in the statistics class for FMM module.
Some more bug fix.
More memory bug fixing for octree. Be careful not to confuse PushBackCopy and PushBackRaw.
Memory bug fully debugged.
Change due to memory bug fix.
Added the bounding box printing
Kind of works, but there is numerical stability issue that I have to work out.
Temporarily turned off all series expansion stuff in DownwardPass_ function to see whether all nodes are being accounted for each query point, and it does account for all. Now need to turn them back on and debug.
Bug fix for list 4 computation for octree.
Crucial bug fix in octree. Bounding box was not being computed correctly based on the z-order code, but is now fixed.
Bug fix in List 1 and List 3 computation. There was a duplicate node issue.
I think it works, now switching back to series expansion stuff.
Turned on the series expansion stuffs, now working reasonably well!
Code restructuring of the inverse distance kernel series expansino stuff.
Added the series expansion convolution pruning for kde cv stuff.
Added the test file for hypercube tree.
Added the parameter to specify the order of expansion.
Added the inverse distance power kernel.
Minor cosmetic changes, but need serious modification of how the approximation is done.
Removed the local polynomial directory, going to start fresh with combined regression/conditional density estimation code.
Initial checkin of local polynomial regression/conditional density estimator code, but it will not compile. I will have to finish it.
Moved a inverse power distance kernel to mlpack/series_expansion.
Relocated the inverse power distance kernel.
General cleanup before the release.
Minor parameter tweaking.
More checkin of the derivative stuff for inverse power distance kernels.
Major cleanup before adding the inverse distance power expansions in Cartesian.
More cleanup.
More draft files added.
More files added.
More templates filled out, but they don't compile yet. I'm in the process of finishing it.
Main driver added.
Added the new files, and now it compiles, now need to actually finish the implementation.
Preprocess/postprocess templates added. still need to finish...
fl-build-all added, modified buildsys.py to generate a custom rule that contains the subrules recursively.
Now compiles, but need to verify that it is working...
Naive module added in, but still debugging.
Namespace for la/blas.h added back in, sparse/trilinos/test.cc compilation error fix.
Minor update to the relative error parameter adjustment such that it guarantees global error.
Bug found, I need to debug now.
Bug found in nwrcde_query_summary
Bug fix in nwrcde_query_summary.h. When incorporating the delta's, we should not add pruned and used error components.
Added relative error computation.
Now supports Epanechnikov kernel, but I need to optimize the pruning rule more.
Memory bug fix.
Took out a commented code.
Upper bound is maintained for denominator sum.
Removed the upper bound maintainers.
Code reduction.
Edited the build file and added monomial kernel expansion.
compilation error fix.
Some bug fix in the monomial kernel expansion, but still in the progress.
Fixed the inverse power distance recurrence such that it correctly computes for r^{\lambda} for \lambda positive as well.
Epanechnikov transform now uses the inverse power distsance kernel expansion. Now need to plug in the error bound stuff for F2L and L2L stuff.
Added the direct local accumulation for Epanechnikov kernel.
Some code reduction, now looking at the correctness of the local expansion evaluation of Epanechnikov.
Bug fix in Epanechnikov series expansion. ComputeDirectionalDerivative needs to compute (-1)^n D_n. I should note this somewhere.
F2L prune enabled for Epanechnikov, it only does exact F2L, approximate F2L will be added later.
Bug finally fixed for Far field to local translation for Epanechnikov. I still need to come up with a good test suite.
Minor change in how inverse pow dist kernel is evaluated for negative lambda.
Compilation error fix.
Now using TKernelAux stuffs to support series expansion!
Minor template typename changes.
Long overhaul to support initializing series expansion objects inside stat objects.
Warning fix.
Move the farfield moments into the reference stat.
Header file clobbering fix. Renamed math.h to math_lib.h, math_impl.h to math_lib_impl.h, and string.h to col_string.h
Some restructuring - moved local expansion from postponed to query stat.
The code should be doing series expansion, but I need to verify it.
Series expansion added for regression code.
Bug fix for Far-to-local translation. I really needed to compute up to 2 * max_order number of stuffs in aux classes.
Series expansion seems to work.
Array index off by 1 error fixed.
Critical bug fix.
--recursive and --help option added for fl-build-all.
Header file conflict change.
Dependency fix.
Various missing dependency fix in build.py files.
Distro build option added.
Fixed it so that it exports built *.a lapack files, but we still need to look at eliminating the need for .lock files.
fx doc fix.
Patched the code for reading in multi-target values per each training point, but currently only supports single target value regression.
Netlib distro of LAPACK/BLAS hardcord g77 as the fortran compiler, overriding the user's preference which might be gfortran. If there is no g77 compiler installed, this would result in failure of compilation. I fixed the build.py so that it replaces the relevant hardcoded compiler choice in BLAS/LAPACK build files using Nishant's suggestion.
Fix to the gradient kernel in Cartesian coordinate.
Multitree template added.
Minor addition to how the gradient kernel can be computed.
Autodetection of curl/wget
auto detecting wget/curl
Various restructuring for performance reason.
Optimized the base code a bit, now starting finite-differene pruning...
Some more fixes.
Naive multibody ported, now have to do finite-difference.
Lower bound accumulated during base computation.
Minor change so that MultiTreeProblem::order is referenced whenever possible.
Some more fix, but I need to make sure that the number of (n - 1) tuples being accounted are coded in!
Pruning function almost done, but need to check and accumulate the number of (n - 1) tuples.
Segfaulting problem fixed.
Now adds up the number of tuples pruned in the base case, but need to put that in the general cases as well.
Some more optimization to compute (n - 1) tuples when computing n-tuples.
Build file fix hopefully for Macs.
Some more changes to do relative error pruning.
Relative error pruning added, but need to confirm.
I think relative error is working!
Naive computation added.
Now computes relative error l1 norm.
Code reduction and cleanup.
Nearest neighbor, futhest neighbor optimization tried, but doesn't make too much difference.
Pruning error fix.
Took out all nearest neighbor optimization, because it doesn't help.
Took out all nn opt.
Now does not approximate the case when one of the nodes is an ancestor of another node in the tuple list.
Monte Carlo sampling needs to be optimized so that it iterates over all points.
Now the canonical case splits and recurses on every node index, instead of splitting one at a time.
Compilaton error fix.
Changed math::Pow<1, 2> calls with sqrt calls.
Now adds up Monte Carlo prune statistics separately.
Now uses 90 % percentile confidence band.
Now the basecase is also rolled up in the recursion loop.
Recmoved the upper triangular square matrix implementation
Build file fix.
build file fix.
now does prioritized dfs.
Modification for multitree algorithms with training labels.
Modification according to multitree template modification.
Change needed to make multibody work.
Multibody code change due to the template class change.
Change to support two-body query reference problems.
Three-body change due to template change.
Change due to the template change.
Template change to take datanode pointer.
Shuffling back the results now according to permutation.
Change due to template change.
Multitree multibody code update, now the Nadaraya Watson regression code is generated from the template.
Code cleanup: took out a dead code.
Now tallies up probabilistic/hard errors separately.
Huge performance tweak based on round-off error detection.
Changed so that the probability is not square rooted.
Fix to the Monte Carlo sampling routine so that it is less agressive.
Prints out how many tuples are pruned.
Now the base of multibody kernel combines positive and negative contributions, but appropriately assigns to the appropriate component.
Some more optimization.
More stable answers, but a bit slower.
Memory leak fix.
Compilation error fix.
Added the template generated KDE without Monte Carlo acceleration, removed multibody code since it is now a part of the fast multipole method package.
Bug fix: The results are correctly shuffled now, using ShuffleAccordingToPermutationColumnwise_
Some crucial fixes to the base case, now need to look at the finite difference case.
Some more changes.
Some more tweaks.
Switched to more aggressive pruning.
Added the static version of the kernel evaluation of the inverse distance kernels.
Big changes with multibody code change, but the multibody code now needs to be an iterative-refinement version.
Commit before iterative-refinement based optimization.
Bug fix in the monte carlo sampling that did not check whether the three indices were out of order.
Scaling option added.
Last commit before relative error incorporation.
Fix to LAPACK build - now forces to use GCC4
LAPACK build fix - forcing the usage of GCC4 and GFortran. Fixes the LAPACK compilation to use -O3 flag instead of -g flag.
Compilation fix for GCC4.
Added the documentation for templatizing matrix and vector to be instances of GenMatrix and GenVector.
Turned off subspace computation.
demo_export.m renamed.
Missing files added.
Current progress - variable values are being passed properly, but need to put default values in CreateFcn functions.
Library problem solved.
KDE bandwidth optimizer call added.
gplot works, but need to have PCA and produce two-dimensional dataset and test on it
Scatter plot for KDE added.
Bill's EMST algorithm added to the demo.
Changec INTMAX to MAX_INT
Remove values.h inclusion.
Probabilistic pruning added.
Removed the makefile since it's auto-generated by fl-build.
Interfaced in PCA, EMST visualization, etc. Now need to incorporate NBC, decision trees, kernel PCA...
Kernel PCA started.
Kernel PCA working, but need to add another button to input the bandwidth value for the kernel matrix.
More work on kernel PCA completed, now onto range search.
Approx rank nn interfaced.
Changed to the general purpose double type, but the driver file should be templatized as well, through fx_param_str fx_root, type, short int
Orthogonal range search interfaced in, now need to do plotting...
Ortho range search visualization added.
Added the plot of rectangle windows.
Probabilistic error computation refined using square root summation.
Lots of things fixed, now need to work on NBC, etc.
Lots of things fixed, but still need to interface NBC and decision tree.
Various changes, bug fixes.
Added more things such as the timing bar.
Added the new file.
Some more changes, now need to look at KDE...
multitree template edit.
Various features added, now verifying KDE.
KPCA fix.
Started adding NBC.
Decision tree aded.
Decision tree output added.
Some changes made.
misplaced parantehesis fixed.
GUI is now resizable.
Path fixed.
library path file added.
textfield resized.
Range button widened.
data file name passed properly from the listbox directly.
Lots of broken things fixed.
color changed.
Commiting what I have so far now, now need to work on NBC... and timings.
Added running/done labels to the figure.
Lots of bugs caught, now need to interface NBC.
Color code added for EMST.
Now plots 5 clusters only.
Textbox output added for each paper reference.
More change to paper ref.
Michael's paper added to KDE.
Sample share need to be worked on.
Compile error fix.
Bug fix on the Monte Carlo pruning where it could have lowered/decreased the tallyed up lower kernel sum bound. Now uses the finite-difference bounds, but more optimization is needed.
Changed the leaf size limit to boost KDE, but need to think about how to also provide speedup for the multibody code...
Template change to compute the exact delta once and share it with the probaiblistic pruning module.
Code change to incorporate the lower bound change in probabilistic pruning function.
Compilation error fix due to template change.
Michael Holmes' nested summative form algorithm initial implementation checkin. Stubs to be filled out.
Some more fleshing out of the necessary prototype functions.
Function operator added.
Index restriction checking need to be verified again probably, but the basic structure seems finished.
Kernel function templatized, supposedly implemented all necessary stuffs to support a doubly-nested naive sum.
KDE CV initial stub added in.
Fixed base/test.h to fastlib/base/test.h in textfile_test.cc
Init function added.
Now I can compute double-sums using the framework.
Monte Carlo compute is now correct, but need a way to dynamically adapt the number of samples.
KDE CV Monte Carlo testing... Now need to add in a stratified sampling with trees.
Started stratified recursive sampling. Still more to fill out.
Added the class representing the strata.
Stratified sampling implementation in progress.
Function prototype change, stratified sampling in progress.
Checking in of the old THOR KDE code.
Critical bug in the base case has been corrected. summary statistics in the base case should have been accumulated after the pruned information is updated, and this is corrected now.
now the base case is replaced by a single-tree traversal, then followed by the inner loop (THOR style). This gives much needed speedup in many cases.
Compilation error fix.
MaxDistanceSq(const double *point) function added. This file really needs a cleanup.
Made the tree types public.
Compilation error fix and basic stratification using priority queue works now.
Monochromatic trick added.
Some fix to incorporate the precomputed number of tuples during computation.
Turned off Monte Carlo probabilistic approximation, now trying to do everything with exact methods.
Initial checkin of the potential evaluation for multibody case.
Shortened kde_problem.h by breaking up into multiple files.
Potential code compiles, but there are stubs to filled out.
The code is compilable, and stubs are being filled out.
First prototype for multibody potential evaluator checked in. Now need to apply series expansion.
Taking out bugs one by one.
Bugs stamped out I think. Need to implement series expansion.
Templatized the computation part.
Chebyshev fit utility added.
LAPACK is built without optimization for Ubuntuu problems.
Error upper threshold could be less than zero (right hand side of the pruning rule), so I thresholded it.
Compilation error fix due to nested sum class change.
Fixed so that it is not templatized in terms of the tree type.
Probabilistic case does not prune when the requirement is 100 % guarantee.
Rough idea implemented.
CFmm tree template added.
CFMM tree in progress.
Some more fixes. Now need to plug in the tree within the tree part for CFMM
Some more brainstoring on CFMM tree... Recursion part needs to be fleshed out...
CFmm Tree compiles but I need to go through again and see if it's working correctly. After that then I have to implement the main CFMM algorithm, which is probably an easy modification of the original FMM.
Segfault fixed, but still need to verify the correctness..
Now need to correct the WS index merging part.
WS index computation added.
Chebyshev fit error computed properly.
Added the stub for continuous FMM, but needs to filled out (rather replaced with a working version).
Some more changes. Now need to work on the bottom-up computation.
Added the link from the WS node to the CFMM tree node.
Added the init flag that tells whether the expansions have been created or not.
FormMultpoleExpansions method completed... Still filling out stubs...
Just have to complete the algorithm...
Templatizing the hypercube tree utility so that it accepts CFMM tree...
Lots of bug fixes on CFMM, now need to optimize.
Base case kernel for the CFMM added.
Some minor changes in CFMM for computing WS index for each node.
Max tree depth added for CFMM tree
Code change due to CFMM tree interface change.
Max tree depth CFMM fix.
Hypercube tree depth limit option added.
FMM edited for adding tree depth limit.
CFMM finished.
Changed CFMM order to 2.
Took out sibling pointer from CFMM tree.:
Bug fix: CFMM tree now uses nonadaptive octree.
Major bug fixes.
Bug fixes.
Final commit of CFMM.
Bug fix in the base case: There was a problem when the distance approached zero, and this is fixed now.
TranslateFromFarField in inverse_farfield fixed. Instead of CopyValues, it should have been AddTo.
Some lower level optimization.
Code compiles, SVDRegress fixed, now proofreading Crossvalidate.
QUIC SVD moved to MLPACK.
Regress and SVDRegress fixed, now the intercept is added to the linear model that is generated at the end.
Crossvalidate function debugged.
Some more bugs shaken out in ComputeSquareError function.
Minor cosmetic change to the driver.
QuicSVD code interfaced.
Monte Carlo pruning plugged in. Now need to debug.
Potential infinite loop fix in Monte Carlo sampling.
Another bug fix in index choosing in Monte Carlo.
Some comments added.
The basic form of feature pruning based on VIF added.
Main framework coded up. Now need to put it in the driver file and debug.
The basic options added to the driver, but need to debug more.
I think cross-validated regression is working. Now need to verifiy VIF feature selection method.
Starting of Fourier series expansion.
Refined Fourier expansion test.
Documentation added, still need to verify feature selection.
Verifying feature-selected regression now.
I have proof-read the variance inflation factor feature selection part.
The test case for variance inflation factor feature selection added.
Some helpful outputs added to the test driver.
Linear algebra directory started.
Some bug fix.
CFMM driver file fix.
Changed int's to short int's for the multiindex mapping to save space. Worked on a bit on Fourier expansion. Now need to work on the error bound.
Fixing Fast Gauss Transform compilation error due to series expansion library update.
Added the implementation of complex matrix.
More progress on the Fourier series expansion (computation of coefficients and evaluation). Now need to plug in the error bound.
Initial checkin of the compressed vector experiments.
Compression and decompression works.
Changed short int to int to prevent overflow.
Bug fix, but compression/decompression overhead seems to be greater.
Testing started for Fourier expansion.
Fourier kernel added.
Fourier expansion being debugged.
Some bug fix in the series evaluation method. I shouldn't have ignored the complex part until all the sum components were added up.
Dependence on dataset_scaler taken out.
Compilation error fix, namespace issue resolved.:
Compilatin error fix due to code overhaul.
Compilation error fix.
Test file for CFMM tree added.
Need to implement method for incrementing the vector.
Disabled multi-threaded builds. Now fl-build and fl-build-all runs with j = 1. This fixes the problems with Opt++
Added in the A^T A SVD method.
Now need to take care of the date features.
PrintDebug for complex matrix edited.
Bug fix in preprocesser. I'm modifying this to save the indices.
The preprocesser utility is done. Now testing regression.
NOTIFY added in some places.
Added the random combination code from Knuth's book.
Some bug fixes in RandomCombination function.
Going to try the point-based Monte Carlo.
The covariance matrix is now precomputed for VIF selection.
Compilation error fix.
Made some fields public
Now reports how many points violated the relative error, and the associated maximum absolute error.
Now reports positive/negative relative error violations.
Moved the covariance computation stuff inside RidgeRegression class. Now need to move the featureselected regression inside as well.
Move the crossvalidated regression inside the RidgeRegression class.
Took out a deprecated function from RidgeRegressionUtil class.
More code restructuring. Crossvalidated regression should be back online.
More code reorganization.
This should fix the annoying initialization error. should_free_ field is set to false when the constructor is initially called. This could be potentially done with the OT-framework using OT_DEFAULT_CONSTRUCTOR macro, but this essentially accomplishes the same thing.
Initial template of CMakeLists.txt added for some of the core directories.
config CMakeLists added.
Finally matches the Vijay's results.
memory leak fix.
Error behavior for Monte Carlo is more reasonable now.
Fix in the Monte Carlo sampling to return positive and negative components separately.
Some parameter tweaking.
Monte Carlo approximation has been changed to per-query estimate.
Added the PostAccumulate function.
Added the option to use different dimension for normalizing.
Checking in linear regression.
VIF initial checkin.
Deleting the makefile.
Restarting KDE.
Attempt to compile boost unit test.
Back to FASTLIB.
Adding the metric object.
Adding L-BFGS optimizer with the test.
Compile error fix.
Fixed L-BFGS test.
Starting multigrid.
More progress.
Adding the test driver for multigrid.
More multigrid.
Sparse greedy GP in progress.
Sparse GPR has long way to go, but I will get there.
Removing old implementations.
Auxiliary files for sparse GPR.
Probably done for today.
Starting clusterwise regression.
More progress on plugging on Smola's sparse GPR.
More progress on clusterwise regression.
Some more clusterwise regression.
More progress.
More progress on sparse GPR.
Slowly plugging in Smola's sparse GPR.
More progress on mixture of experts.
More progress.
Astyled.
Getting there.
Getting infinitely closer.
Need to just write the driver for clusterwise regression.
CMakeLists.txt updated.
Slowly plugging in the driver for the clusterwise regression.
Close to finishing the driver.
Still fixing bug.
Clusterwise regression should work, but needs testing.
Getting closer to finishing Smola's
Getting closer.
Almost ready to finalize Smola's sparse GPR.
carefully verifying Smola's method.
Still debugging.
Plugging in mean/variance prediction for sparse gpr.
Minor edits.
Fixing.
Getting there.
Smola's method should be complete.
Adding the driver for GPR.
Compile errors are gone.
Finished the crucial part for multigrid.
In theory, the coarsening procedure of multigrid should work for dense matrices.
Compile fix.
Still debugging multigrid.
Still debugging.
Still debugging, need to look at the coarsening procedure.
Test.
Pseudo fastlib checkin.
Fix
Checking in thesis research code.
Fix to the CMake.
Prefix scan code added.
Starting distributed tables.
Adding the test for distributed table, will finish today.
Fixing warnings.
Removing old directories.
Fix to CMakeLists.txt which I never use.
Getting there.
Getting closer to distributed table server.
Kind of works, now have to test.
There is a bug, I am fixing it.
Fixing.
Getting closer.
I think it works.
Will finish today.
It works, now ready to build the distributed tree.
Fix to CMake flags.
Currently fixing the deadlock.
Fixed, now really ready to start the tree.
Will need to fix the test so that it is more informative.
Changed the prototype for initializing a distributed table.
Potential race condition fixed.
Bug fix.
Took out efence.
Dividing up files.
Some obvious variable elimination.
Fixing the distributed table with more threads.
Will continue tonight.
The new distributed table is on the way.
Almost fixed.
New implementation to be debugged.
Still deadlocking, but very close.
Will continue tomorrow.
Still fixing bugs.
Getting closer.
Fixing again.
Inbox/outbox merged.
Minor bug fix, now plugging back the point server.
All fixed.
Starting distributed tree building.
Slowly plugging in distributed tree building.
Will restart tomorrow.
Still fixing.
It turns out my MPI implementation supports only single-thread, so I need a mutex around MPI_IProbe.
Put locks around each MPI calls.
Extended the tree building to allow up to only a fixed number of leaf nodes.
Serializing the tree so that it can be transferred.
Tree building almost done.
Getting closer.
Getting there.
Will fix at home.
More bugs fixed.
Fixed a dumb bug.
I think the distributed tree building works.
Restarting three-body so that I can finish submitting the paper.
Plugging back in the three-body recursion.
More work on 3-body.
Back to distributed tree.
Fixed the serialization for trees.
Serialization for tree fixed.
Almost there.
Fixed the deadlock issue.
Slight deadlocking problem in investigation.
Switching to memory mapped file.
Fixing compile error for kde.
Fixing interprocess communications.
Slowly changing the model.
Will finish later.
Compile error fixed and fix such that the tree can be put under the memory mapped file.
Full fix, now ready to plug back in the distributed table.
Extension to support memory mapped file.
Slight problem, so need to fix it.
One mistake found.
Crucial bug fixed.
Bug fix.
Another fix. Now ready to get back to distributed table.
A little tweak.
Getting there.
Now ready to plug back in the mailboxes.
Three-body compiles, now finishing up so that I can finish writing the journal paper.
Will continue tomorrow, very close.
More progress.
Getting there.
Plugged in the pruning for three-body, need to debug.
Will continue tonight.
Added a timer class.
Just have to plug in Monte Carlo into three-body, rerun experiments, and publish and graduate.
Adding the test for three-body.
Three body test compiles.
Script for backing up thesis code.
A little tweak on the script.
Will continue tonight.
Adding the random combination generator to math_lib.h
Fixing compile error.
Plugging in Monte Carlo into three-body.
Moving directories.
Slowly plugging in.
Will continue soon.
MC three-body.
Fix to the three-body, still working on Monte Carlo.
Compiling.
Compile error fix.
Will continue tonight.
Will continue tomorrow.
Slowly making some progress.
Slowly finishing.
Compiles now.
Progressing.
A bit more progress, so close.
Kind of done with Monte Carlo three-body, will check tomorrow.
Crucial bug fix.
There is a bug in Monte Carlo three-body, so need to fix it tonight.
Will continue tomorrow.
Fixing bugs.
More bugs fixed.
slowly looking at things.
Probability redistribution should be working.
Quick bug fix.
Restructuring Monte Carlo.
Still tuning Monte Carlo, the most painful part.:
Monte Carlo part divided into positive/negative parts.
Tweaked the Monte Carlo a bit.
Another bug fix.
Removed a warning.
Some tweak.
Adding in the modified LMetric for distance thresholding.
Will debug tonight.
Fixing.
Resolving some problem with numerical stability.
Trying to fix the inf problem.
Eliminating dead code.
Less aggressive pruning rule, will try to do the quantile idea for maintaining lower bounds.
Will fix soon.
Crucial bug in CSV parser was fixed - before it did not consider a space as a delimiter. I would consider replacing the CSV parser soon with something more stable.
Fixed the test for three body.
Adding in the quantile based pruning.
Tweaking Monte Carlo.
Bug fix.
Some tweaking.
Seeing the light at the end of the tunnel.
More tweaks.
more
Crucial bug fixed.
Increased the number of points in nbody_simulator-test.
Will continue later today.
Monte Carlo pruning picks up right after the node which fails.
Minor edit.
Added the statistics report for prunes.
Naive point dimension check.
Minor edit.
Still tweaking.
Slowly adding the quantile prune.
More tweak.
Have to get finite difference to work.
Kernel bounding for AT modified.
One final Monte Carlo tweak remains.
More tweaks.
Will continue today.
Finite difference fix for three-body, almost getting ready to run the experiments.
Will add kd-tree now.
Adding in the kd-tree.
Slowly adding in
Templatizing the table made this painful.
KDE compiles again.
Other tests compile now.
Major surgery to get kd-tree integrated.
Three-body code now uses kd-tree.
Kd-tree bug fixed.
Added the Monte Carlo trick which would benefit for large number of points case.
Crucial bug fix for node tuple.
Monochromatic trick added for three-body.
Some fix.
Very obvious optimization.
Getting to the HPC project.
Going full speed.
In progress.
Debugging.
Still fixing.
Doesn't segfault.
Boost Interprocess sharing works, but needs deep structuring to make sure that there are no virtual classes. The tree needs to have offset pointers.
Clears out the temporary file before each run.
Don't ever put raw pointers inside memory mapped files
Starting HPC homework 6.
Done with HPC HW, now have to write the report.
Fixed the homework.
Back to parallel kde.
Optimizing serial kde.
Support code to run the final experiments.
Support code for three-body in progress.
In progress.
Support code complete, now just have to run the experiments.
Adding GP regression.
Some edit.
Back to my ultimate weapon, distributed kde.
I'll get there.
Fixing the communications tonight.
Trying to get communicator (inter) working.
Getting there.
I think I can start the HPC project.
I will fix it today.
All fixed, now moving onto more interesting things.
Renamed the directory to distributed_kde.
Makefile change.
Namespace fix for serial kde.
Starting HPC project.
Restarting distributed tree.
In progress.
Unabstractifying so that I can use boost interprocess.
Fixing tests so that they compile.
Fixed so that no virtualization is allowed inside the memory mapped file.
Compile fix, now back to distributed kde.
Getting rid of warnings.
Getting there.
Segfault fix.
Will continue.
Fixing Monte Carlo for three-body, have to rerun the experiments.
Getting there, believe it.
Serialization for tree in progress.
Slight problem, will fix soon.
Fixed the monochromatic case for three-body.
CMakeLists fix.
Another crucial bug fix.
Problem encountered, so reverting back.
Another bug fix.
Some bugs fixed, but getting there.
Clear error in template instantiation, so fixed in distributed_kde.cc
AbstractStatistic added serialization.
Fixing the segfault.
Bug fix.
Bug fixed, never mix destroy_ptr and allocate.
Going to implement distributed hungarian algorithm.
Still in progress.
Rename.
Will continue tomorrow.
Going.
Fixing, almost there.
Distributed auction seems to work.
Minor cleanup before finishing up the distributed tree.
Slight problem, so have to fix.
Fixing bugs.
Continued later.
Adding distributed local kmeans.
CMakeLists.txt edit.
Will continue later, now the multibody multipole.
Going.
Will continue later.
Need to debug.
Some bug fix, now have to add in the distributed indexing of the points.
Bug fix.
Getting there.
Compiles, but still on progress.
In progress, but getting there.
Getting there.
Moving the points across the processes work, now need to send over the indices too so that they can be reshuffled.
Templatized the indexing type in tree building.
Deep changes in how the indices are maintained in the table.
Some changes.
Adding L-BFGS.
Fixes so that optimization test compiles.
Continue tomorrow morning.
Top tree should work now.
Critical bug fix.
Another critical bug.
Trying to fix.
Getting closer to fixing the bug.
Should be all fixed now, now ready to start the fun part.
Minor fix.
Distributed kde to the finish line.
Intercommunicator example added.
Starting again.
Took out armadillo from distributed table.
Starting on the distributed kde driver.
Trying to make the distributed_kde driver.
Serialization for table should work in theory.
Added the pointer correction.
Adding the distributed dualtree algorithm template generator.
Distributed kde driver almost operational.
All fixed, now ready to work on the distributed dualtree.
Starting to fill up distributed dualtree template.
Getting there.
Some edits.
Another edit.
Compile error fix.
Compile error fix.
Added the serialization for dense matrix, finishing up the distributed dualtree computations.
A little dinner break, then continue bashing.
Almost there.
Compile error fix.
It runs.
Continued later.
Some bugs in distributed kde, but it runs without crashing.
It runs. Now have to check correctness, and make the poster.
KDE test fix.
Deadlock fixed, now adding in the test driver.
Fixing the monochromatic case for KDE/distributed KDE.
Compile error fix on dumbledore.
Minor format change.
Minor compile fix.
Timer calls.
Timers.
Default bandwidth value changed for experiments.
Some tweaks for experiments.
Another tweak in distributed table before parallel ssample sort implementation.
Added the prune statistics.
Hopefully this fixes.
Closer.
Last change before tweaking the allreduce part.
Minor fix.
Warning fix.
Cleaning up so that MPI KDE can run without memory mapped files.
Compile error fix.
Some fixes to KDE, now adding in the distributed table test.
Fixing in the distributed kde test.
Trying to make the test pass, but this will be the checkpoint for the code submission.
Still trying to match.
Distributed kde test passes.
Critical bug in distributed tree building fixed.
Mixed Logit started.
Warning fix.
Getting there.
Getting there.
Checking in the DCM table.
More work.
Trust region almost done.
Some code restructuring.
Compile error fix.
Warnings fixed.
Almost there.
Dinner.
To be continued.
Back to N-body
After dinner to be continued.
Added matrix generalization of mean variance pair.
Subtable view seems to work.
Some output fix for distributed kde test.
In progress.
More brainstorming, back to distributed kde.
More work, back to distributed system.
WIll come back today.
Now distributed kde can run on number of processes not equal to a power of two.
Fixing.
More progress.
More parameters added.
Going.
Starting matrix triple product.
Fixing the compilation error, and subtable capability added.
Minor compile error.
Random number generation in fix.
Going.
Getting there.
Compiles, will continue tomorrow.
More progress.
Plugging back in trust region code.
More cleanup.
Will continue tomorrow.
Taking out deprecated functions, trying to eliminate DensePoint/DenseMatrix classes.
Armadillo-ifying the L-BFGS.
Will get rid of densepoint and densematrix and linear_algebra.h
Going the wrapper approach in dense point to use armadillo operations.
Bug fix.
Armadillo-ifying
Kind of compiles.
Compile fix.
More progress.
Code restructure.
Sampling class separated.
KDE compile fix.
Another.
Will continue after lunch.
To be continued.
After dinner.
Will continue tomorrow.
Mysterious crash in distributed kde memory mapped file mode fixed.
Fixes before trying the new distributed gnp.
Sub dense matrix added.
Astyle fix.
Another check point.
Another checkpoint.
Another checkpoint.
Another checkpoint.
Another checkpoint.
Another checkpoint, getting closer.
Checkpoint.
Another checkpoint, getting there.
KDE now supports progressive computation.
Checkpoint.
Done for today.
Getting closer, now have to fix the segfault.
Almost there.
Almost there.
Memory leak fix in distributed kde code.
Need to ask.
All bugs fixed, now just have to do performance tuning.
Crucial bug in the distributed kde test.
Found the mistake.
Some problems, will fix today.
Found the problem, will fix later.
I think all fixed, now onto performance tuning.
Adding in the distributed parallel triple tree.
Some minor correction.
Need to look at the tree building now.
Test fix.
Parallel sample sort in progress.
Will continue later.
CMakeFile fix.
More progress.
Testing the parallel sample sort.
To be continued.
Distributed sample sort works, now have to rewrite distributed tree building.
Going.
Another compiler error fix.
Compile error fix.
Refactoring the distributed tree builder.
Will continue tomorrow.
Distributed tree in progress, added functions to generate points within a bound.
Adding the distributed tree test.
Armadillo change for 1.0.0 incorporated.
minor fix to CMake in the core.
Getting there.
Minor fix.
Will continue soon.
Some files reshuffled.
Bug fixed, now finishing up distributed tree and new FMM.
Complie fix for distributed tree builder, still in progress.
Added the random point generation test for bounds.
Final compile fix before dinner.
Getting there.
Devirtulaization of metrics.
Compile error fix.
Another fix.
Final fix.
Another fix.
Done for tonight.
Have to fix the segfault in distributed tree.
Critical bug fixed, still looking at distributed tree.
Bug fixed, still continuing the parallel tree, but almost done.
More progress.
Almost done with parallel tree.
Will continue after lunch.
Experimenting with gcc garbage collector.
Quick patch.
Added the bound inclusion test, now finishing up the distributed tree.
Done for tonight.
Lots of bugs fixed. Almost done replacing the distributed tree.
Lots of bugs fixed again, but very close to replacing the distributed tree building.
Cleaned up distributed tree builder.
Adding more comments. Now ready to improve the distributed engine.
Further code reductino.
Compile error fix.
Need to test the Morton ordering, and refine the tree building and the distributed framework.
Trust region being debugged.
Need to plug in Hessians for test functions.
Fixing the bugs.
Trust region kind of works, but convergence is slow.
Added different methods for trust region search.
Took out prints.
Some trivial changes, before distributed overhaul.
One critical bug fixed in distributed GNP, where the reference tree was grabbed multiple times.
Added the prioritization for distributed computation.
Bug fixed. Now need to deal with the MPI message sizes.
Lots of improvement.
Rewrite of Cartesian series expansion using boost multi-array in progress.
Series expansion library being integrated into the new library.
Removing deprecated files.
Slowly porting farfield expansion.
Combined series expansion auxiliary classes into one, code compression in progress.
Some overhaul.
Another checkpoint.
More progress on FMM cleanup.
Now need to work on local expansion.
Copyright updated.
Will continue after lunch.
Added the sanity test for three-body.
More surgery.
Almost there.
Complie error fix.
More overhaul, getting closer to cleaning up series expansion.
Almost done cleaning up Cartesian series expansion. Now have to work on the test driver.
Compile fix.
More fixes.
The global mapping test for series expansion passes, now plugging in farfield and local expansions into the test.
Slowly fixing the compile error.
Getting the test to work.
Epanechnikov expansion test added.
Testing the farfield expansion.
Done for tonight.
Slight bug in p to the d, will fix today.
Series expansion bugs in p^D fixed.
Minor fix.
Quick fix.
Changed distributed dualtree to use priority queue.
Compile error fix on Hogwarts.
Another.
Another.
Another fix.
Short comments.
More commenting.
Adding in the absolute error approx.
Going.
Quick tweak.
Fixing the pruning rule.
Starting kernel independent FMM.
Will finish
Some bug fixes. Now that we are using a pq, we need to maintain the subtables from previous round, but need to think about throwing out old-unused tables.
Warning fix.
Need to write a non-sampling based binary tree builder.
Prioritization changed.
Bugs fixed, now have to check that subtables are not grabbed multiple times.
I will be back.
I will be really back.
More patches.
Warning fix.
Compile error fix.
Boosted the number of points in distributed kde test.
Some more commenting before the naive parallel tree building.
Some more changes, now onto new parallel tree building.
Trying to add in the vanilla distributed tree builder.h
Done for tonight, will continue the distributed tree (vanilla).
Getting there.
Compile error fix.
Gettiing there.
Another compile error fix.
Back to parallel tree.
Going.
Adding in the vanilla distributed tree builder.
Going.
Getting there.
Going.
Some minor changes, before optimizing the distributed GNP.
Some mini patches.
Some code optimizations/cleanup done on the distributed framework, now need to replace the cache with a circular buffer.
Re-debugged, now have to change to the circular buffer.
Back to mixed logit.
Back to circular buffer for the moment.
Circular buffer added, subspace tree being revived.
Adding in the distributed allknn driver.
I will continue tomorrow.
Bug fixed. When the all-to-allv was being called, subtrees belonging to another subtree wouldn't serialized, so a post-correction step was necessary.
Test fix.
Take two on the circular buffer patch, hopefully this passes the test.
Test trial updated.
More documentation.
I will continue tomorrow.
Adding distributions.
Back to distributed tripletree, my secret weapon.
Minor bug fix.
More work.
Back to parallel.
Adding a new script.
Further proof-reading.
Minor edits.
More comments.
I will continue after dinner.
Bug fix in the ball bound random point generation.
Optimized so that new_from_old mappings are not sent for subtables.
Kd-tree added in the test mix, plus now attempts to split everytime until the number of points is below the threshold.
Changed so that the cache size is somewhat constrained per process.
I think the leaf size now should be uniform across all MPI processes for distributed algorithms, so I fixed it.
Getting into the subtable test.
Turned off tracking for GeneralBinarySpaceTree to avoid subtle bugs in boost serialization/mpi.
Removed the print statements.
Ready to go to Dumbledore.
Need to restructure the algorithm.
Quick change.
Small tweak.
More tweakk.
Minor changes.
Numerical issue solved.
More errors fixed.
Another.
Parallel tree building.
Distributed tree building in progress.
Serialization for LMetric.
More patches.
Fixing the distributed engine now.
More bugs fixed in parallel tree.
More bug fixes.
Compile error fix.
Some changes in the distributed tree build.
Some performance problem. I am looking into it.
Compile error fix.
Going back to the former, now have to choose one reference tree to compute at a time rather than expanding the entire priority queue.
More tweaks.
Now, the priority queue is only expanded only one at a time.
Bug fix.
No more caching.
Need to investigate the slowdown.
Memory leaks fixed.
Minor fix.
Minor patch.
fixing.
Bug fixed in uninitialized stack allocation. The problem was that I forgot to pass in the absolute error value criterion.
Minor change in kde test.
Back to vanilla.
Tree serialization is more efficient now.
Took out a print statement.
Fix in the pruning condition which was introduced when the hybrid error condition was plugged in.
Minor compile fix.
Some bug fixes. The query stats were getting resetted during the distributed computation.
Subtable test fix.
Crucial bug fix - table lookup was too slow in the previous version.
Minor edit.
Changing the tree.
Changed the leaf size.
Templatized the kernel type, and now plugging in the series expansion.
Removing abstract kernels, now everything is template.
Fixed a bug in kde-test.
Pushes in the right expansion type.
Templatized the series expansion object for kde.
Slowly plugging in series expansion.
More restructuring.
Quick fix to a test.
Memory requirement for series expansion fix.
Slowly adding in series expansion, almost there.
A little break.
Almost there.
Series expansion is now plugged in, now have to debug.
Series expansion should be functional, but really need to go through and verify and debug.
Bug fix.
Counting the number of prunes.
Problem with multivariate gaussian expansion, will fix soon.
Disabled the Epanechnikov expansion until further notice.
Fix due to the templatization of SphereVolume function.
Took out geometry.c and geometry.h
Bringing back the distributed kde with series expansion.
Adding in the scale option.
Distributed kde/test compiles again.
Parsing error fix.
Timer added to the KDE.
Argument parser separated for mixed logit.
Porting Bengio's method for the finish.
Added the approximate Hessian update routines.
Added the method for determining whether there are points underneath an arbitrary node in the tree.
Segfault fix for distributed kde.
More debugging.
Temporarily turned off non-uniform weight series expansion.
Mistake in the series expansion fix, now have to make sure that the rpoints are properly accumulated in the case when the table stores non-contiguous points.
Minor corrections.
Changed the AccumualteCoeffs to use iterators.
Took out a useless operation from kde_dualtree.h
Found a bug in multivariate series expansion that involves copy constructor of core::table::DensePoint. Must be careful when using core::table::DensePoint since I define assignment operator in a different way.
I found out that the series expansion does not work properly under distributed setting, so coefficients must be not being cleared/exchanged. The distributed_kde-test now forces the exchange of entire trees.
CMakeLists.txt modified to accept CMake 2.6
Now copies farfield expansion when statistics are copied for KDE stats.
Added the copy method for copying the farfield expansion.
Changing the test to do level serialization for distributed kde test.
Now grabs every table from the distributed computation in each stage, might have to threshold this later.
More subtable test.
Cache size constraint.
So there is a problem with the node iterator in the subtable, so I'm fixing. After that everything should work.
Corrected the subtable iterator test, still debugging.
Bugs in subtable node iterator fixed.
Took out debugging statement.
Adding the depth function to GeneralBinarySpaceTree class.
Compile fix.
Another fix.
Fix.
Final bugs fixed, now have to look at the iterator performance for the subtable.
Memory leak in distributed_kde-test fix.
Minor indentation fix.
Added the quasi random number generator, which needs to be tested later.
Probably need to change the quasi-random generator with QuantLib.
Fixing the problem in distributed kde where multiindex mapping was computed multiple times.
Monte Carlo scratch space for MCMM is allocated only once for distributed version.
Finishing Bengio/Smola expansion so that I can write my SC paper.
Finishing Bengio.
I will continue today.
Getting there.
Getting there.
Reshuffling should work for weights theoretically.
Weights are now retrieved from iterators in FMM.
Renamed the files.
Getting there.
Getting there.
I think almost done.
Eliminated a useless function.
Quick fix in arma::submat use.
Plugged in quasi newton updates.
Plugged in the distributions.
Getting there.
Correction.
Ready to start the test driver for mixed logit tomorrow.
Starting the mixed logit test.
Test compiles, now have to run it.
Getting ready to run the test.
Almost there.
Typo fix.
Bug fix.
More fixes.
Fixing.
Still crashes.
It runs, but I have to check that it terminates.
Some correction.
Adding debugging statements.
More messages.
Almost.
continued after dinner.
Fixing the memory bug.
Made the destructors virtual, but really need to think about making it a template distribution.
Memory leak fix.
Changed the virtual functions to traits for performance.
Compile error fix.
integration sample size for multinomial logit fixed to 2.
Working.
Something runs.
Going.
Fixing.
Almost there.
Minor comments.
I think I derived how to evaluate the dictionary compressed far field moment expansion.
Going.
Starting the F2L translation operator.
Slowly getting there, too tired.
Code restructuring in Bengio FMM.
Finishing up F2F translation operator for Bengio so that I can start writing.
Seems to be working, now have to plug it in.
It seems to be working.
Fixing the CMake.
Fixed a bug to make sure that the weights are serialized as well.
Bug fix in monte carlo kde.
A utility function added to GeneralBinarySpaceTree.
Bug in the max prioritiy queue fixed.
Some changes.
Prioritization added.
Memory corruption fix.
Fix.
Fix.
Fix.
Changing to kdtree.
Changing to sample based tree builder.
Fix.
Fix.
Fix.
Tweak.
Going.
Tweak.
Fix.
Warning fix.
Fix.
Another.
There is an load imbalance.
Extrinsic prune added for kde.
Trying out new things.
Fix.
Bug fix.
Some restructuring.
Fix.
Getting there.
Hopefully this fixes things.
Change.
Final.
L-BFGS fix.
Simplified the design of distributed dualtree algorithms.
Fixing the test.
Bug fix in distributed kde.
Took out debugging statements.
Another debugging statement.
Going back to the previous.
Previous.
Bug fix - self contribution is now subtracted only once.
Seeding added for distributed computation for extrinsic prunes.
There.
Monte Carlo fix.
Hopefully this fixes the out-of-memory problem for 512 processes.
Bug fix.
Buffer size is fixed now.
Starting random feature.
Performance bug fix.
More progress on random feature.
Compile fix.
Random Fourier feature seems to be working.
Fixing Rahimi.
Fixing the series expansion test.
Bug fix in RandomPick.
Fix in Monte Carlo.
Added the probabilistic prune counter.
More fixes.
Changing default option.
Obvious monte carlo fix.
Another fix.
Compile fix.
Minor.
Now reporting prune statistics for distributed kde.
Monte Carlo problem fixed.
Adding unithypercube scaling options.
Prints the initial frontier size.
Changing to kdtree.
Bug fix in distributed kdtree building.
Tuning.
Warning fix.
Changing options.
More tweaks.
Some changes.
Adding extrinsic prunes on the global scale.
Adding default absolute error.
Prioritization on the global scale added.
Formatted.
Slight change.
Compile fix for KDE.
Turning off scale for distributed kde.
Starting distributed kpca for SC paper.
Doing distributed KPCA.
Going.
Getting there.
Continuing at home.
Continuing soon.
To be continued. Will finish today.
Getting there.
Getting.
Getting there.
Close to graduation.
I think it works.
I think it works.
Getting there.
Warning fix.
Another warning.
Bug fixes.
Need to fix compile error.
Compile fix.
Bug fix. Normalization added for KPCA.
Different outputs for each process for KPCA.
Minor debugging statements.
Gradually moving toward sampling both in data space and function space.
Crossing fingers
Fixed.
Fixing.
Bug fix.
Starting KPCA distributed computation part.
Will continue later today. Almost done.
Slowly finishing.
KPCA step almost done.
Getting there.
ALmost.
Almost there.
Cleanup.
Just need to finish one part.
Added the copy constructor/assignment operator to MeanVariancePairMatrix.
Getting there.
I will continue soon.
Should be ready to run on the full KPCA mode.
Getting there.
Almost runs.
Memory leak fix.
Almost done.
Almost there.
Getting there.
Fixing the KDE mode bug.
Almost done. Now adding the centering.
Starting the centering.
Restructuring.
Almost there with the centered KPCA.
Almost there.
Done. Need to debug now.
Adding KPCA component vectors normalization.
More bugs fixed.
Getting there, almost.
Adding the naive mode.
Good news is that the naive seems to match.
Bug fix.
Lots of bug fixes, almost there with distributed KPCA.
Bug fixes, should be ready to start running by Wednesday.
Committing.
Took out exit.
Compile fix.
Small parameter tweaking.
Should be ready to run the experiment.
Almost ready.
Critical bug fixed in KPCA centering case.
Warnings fixed.
Debugging statement taken out.
Last change.
Took out a debugging statement.
Adding threads to distributed KPCA.
Fixing silly mistake.
ANother error.
A bit of restructuring.
More stuffs.
Added threading to the convergence check part.
Adding the new convergence check file.
Crucial bug fix.
All done, some sanity checks are in order.
Memory leak fix.
Another bug fix.
Now turned off the random generation mode.
Fixing an error.
Another mistake.
Seems all bugs are fixed.
Should be able to read one file across multiple MPI processes.
Now outputs to different files.
Bug in the driver fixed.
Postscaling added.
Minor change
Changing.
A little tweak.
Another tweak.
Is it working
Going Pthreads.
Changed all calls to pthreads.
Hypercube scale fixed to prevent division by zero.
Now has the option to take a real dataset and grow up to a prespecified size by adding random gaussian noise.
A quick fix to make sure that growing the file is done in parallel.
Quick bug fix in naivekerneleigenvector in non-centered case.
More numerical stability added to the centered case.
Fixed the centering bug in KPCA.
Changing the perturbation.
Should run faster.
Serious performance bug in threaded code fixed. Now the main thread goes after the children are launched.
OpenMP-ified.
Bug fix in openmp part.
OpenMP retake.
Should read in faster now for KPCA testing.
Dataset reader compile fix.
Adding the training error measure.
Continued later.
Splitting file optimized.
Timer added.
To be continued tomorrow.
Getting there.
Fix.
Fix.
Format.
Bug fix in random combination generator. Added the option to clear or not clear.
Format.
Turned off probability allocation for three-body.
Fix.
Bug fix in three-body Monte Carlo.
Adding local regression.
Fixing argument list for mixed logit.
The test sets are now read in.
Tomorrow.
Changed to use boost scoped array.
Should fix the numerical stability problem. Will debug tomorrow.
Took out exits.
Bugs fixed.
Another bug.
Test.
Bug fix.
Another.
Bug fix.
Fixed.
Still debugging algorithmwise.
I think constant distribution is fixed.
Main driver.
Took out the statement.
Some optimizations.
Added the diagonal gaussian distribution.
Back to distributed nbody and adding OpenMP parallelism to finish all of it.
Changed the function for grabbing subtrees so that the size is limited.
More changes.
OpenMP shared memory parallelism added to distributed GNP.
Bug fixes.
Number of threads option added.
Bug fix in KDE. Still need to fix more.
Bug fix in the dualtree_dfs_dev.h. Compute function needed to consider pairwise distance between query_start_node and reference_start_node.
Fixing mixed logit sampling problems. Still need to look at more.
Some optimizations for mixed logit.
Default option is now bfgs.
Optimizing.
Bug fix in diagonal gaussian.
Changes.
Another bug in diagonal Gaussian fix.
Some fixes.
Dividing up code.
Specialized so that the integration samples are always 0 for multinomial logit case.
Some fixes.
Getting there.
Getting there.
Some changes.
Now reports the maximum number of integration samples in use.
Putting back in the gradient error computation by formula.
Transitioning.
Added the function to return the set of sample mean variances in meanvariancepairmatrix object.
Limits the integration samples per person.
Getting there.
Updates the approximate Hessian in every iteration.
Compile error fix on no.
Adding weighted Lmetric.
Trying to revive the kde crossvalidator.
Starting local regression.
A little fix in the distributed dualtree to maintain one computation frontier per each MPI process.
New local regression in progress.
Filling out the dualtree stub for local regression.
Fixing local regression.
Fixing local regression part 2.
Additional argument to the mixed logit code for deciding how to compute the errors.
Moved the serialization of arma::vec to core::table. Added the serialization of arma::mat.
More stubs filled out for local regression.
More.
Compile error fix.
Will be back.
Compile fix.
More.
Continuing tomorrow.
Will be back after lunch.
Compiles, but need to make another pass.
Compiles finally, but still debugging.
Fixed the parser for local regression.
Segfault fix.
Some bug fixes, getting local regression to work.
Switched the initialization order of query tree and reference tree.
More fixes.
Dualtree modification for query result initialization.
modification for query result initialization.
Prints out the number of dimensions parsed.
Adding the test mode for mixed logit.
Mixed logit adding the test mode.
Slowly adding in the test mode.
Compile error fix.
Modification to the dualtree generator.
Modification to the local regression so that it computes the final regression estimate.
Mixed logit test compile fix.
Writing the local regression results to the file.
CombineWith function MeanVariancePair is fixed such that if the incoming pair is empty, then it returns.
More edits to local regression.
Added the method for downdating the Monte Carlo sampling.
Changed so that coordinates are non-negative for local regression.
Nonnegative transform added.
Adding the Monte Carlo test.
Local regression being fixed.
I think it work finite difference-wise.
Adding the NWR mode for local regression.
Modification to dual-tree generator to support NWR.
NWR should work now.
Bug fix in local regression post-process.
Bug fix in local regression. Still debugging.
Ready to test NWR.
Table class changes to add method for returning point weight.
Adding the local regression test.
Local regression test added.
There is a bug in the table which needs to shuffle the weights as the points as the tree building is done. Will fix now.
Fixed the tree building to shuffle the weights as well.
Fixed the local regression test.
Trying to pass the local regression test.
Bug fixes in local regression. Gaussian case works now, have to fix for Epan Kernel.
Fixing the pruning rule for monochromatic case, then moving onto Monte Carlo version of the algorithm.
Getting there.
Local regression fixed, now plugging in Monte Carlo.
Weighted metric added for local regression.
Extensions for weighted metric.
Fix.
Fix to uninitialized values.
nonnegative transform only translates form negative mins.
Trying to fix local linear bug.
Local linear bug fixed for fixed bandwidth. Works perfectly, but still need to add Monte Carlo in a clean way.
Broke the files into smaller pieces for local regression.
Broke kde into several parts.
Pluggin in Monte Carlo for local regression.
Restoring CMakeLists.txt
Almost done adding sampling for local regression (Gaussian kernel).
Fixed the monochromatic case for KDE, now back to local regression Monte Carlo.
Bug fix in distributed kde test.
Getting there in finishing up sampling based local regression.
Will debug later. Almost done with Monte Carlo sampling in local regression.
Almost done with Monte Carlo local regression.
Getting there. Should be ready to run the mega-scale experiments in a month.
Fixing the compile errors.
Fixed the compile error for local regression, now just have to debug/verify.
Starting the CUDA version of KDE.
CUDA fix.
Adding the CUDA kde driver, now starting naive CUDA kde.
Finally linking CUDA, but still in progress for naive GPU KDE.
I will continue tomorrow.
Now running local regression to verify Monte Carlo.
Compile error fix.
Added the probability argument for local regression.
Debugging Monte Carlo sampling in local regression.
Monte Carlo seems to work.
Almost done setting up CUDA kde.
CUDA kde almost done.
I will test on the GPU now.
Getting there.
Fixing the CUDA KDE.
Bug fix in CUDA kde.
Debugging.
Debugging CUDA again.
Getting there.
CUDA KDE works.
Bumped up to 512 threads for CUDA kde.
Relaxed the pruning rule for NWR.
Adding the distributed local regression driver.
Bug fix in distributed tree in progress. One more bug to fix there.
Possible race condition in distributed tree building. Barrier before refreshing the number of points.
Fix in the distributed tree building. Should return false when failing to split points.
Distributed tree building should work more or less.
Added the multi-threaded tree building. Now onto GPU-based tree building.
Fixed omp for to omp parallel for.
Distributed local regression compiles now.
Warning fixes.
More warning fixes.
More warnings.
More warning fixes.
Multithreaded tree building enhanced.
Testing the distributed local regression.
Compile error fix.
Another fix.
Fixing the subtable test to compile.
Debugging distributed local regression.
Ultranaive for local regression factored out.
Re-factoring the test driver for kde/distributed_kde.
Bug fix in multi-threaded tree building.
Multithreaded tree-building fixed.
Need to fix distributed local regression, then back to CUDA.
Fix in the distributed local regression.
Distributed local regression test runs, but does not pass yet.
Duplicate option in distributed local regression cut.
Distributed local regression test still does not pass yet.
Distributed local regression test passes now.
ifdef added for OpenMP.
Fix.
Fix.
Boost anycast error fixed for dist local regression.
Fix.
Fix.
Fix to the subtree size so that more cores are utilized.
Change so that multi-threading assigns a unique core to each query subtree.
Fix so that division by zero does not happen in NWR.
Fixing the distributed tests.
Starting the randomized range finder from Halko's paper.
Finished adaptive randomized range finder, now have to test it.
Testing the random linear algebra stuffs.
Halko's algorithm completed, now ready to plug into KPCA/GP.
To be continued tomorrow.
Randomized power iteration works.
Test.
Starting the GP regression driver.
Deciding on the final algorithm formulation for GPR.
Starting ADMM distributed optimizer for GPR.
Adding in sender-initiated asynchronous distributed GNP engine.
More.
N-body engine now uses asynchronous communication so that computation can be overlapped better.
Moved distributed engines to core/parallel.
Now have to fix the load-balancing issue, and done with 2-body distributed GNP.
Need to fix the load balancing issue.
Bug fix which resulted in non-termination when extrinsic prune occurred using the global tree.
Adding the dual-tree load balancer.h
Compile error fix.
Parallel METIS cmake finder.
ParMETIS works, now have to use that to do load-balancing.
ParMETIS edge weights are always positive integers.
Giving up on ParMETIS since it segfaults, doing naive load-balancing.
Naive load balancing.
Slowly transitioning to the load-balancing scheme.
Bug fixes.
Ditching the static load balancing and implementing the receiver-initiated load balancing.
MPI timer measured for each MPI process.
Slowly transitioning to the receive oriented load balancing scheme.
Eliminated useless variable from TableExchange.
Adding new messages.
New file.
Slowly getting to a smarter communication pattern.
Compiler warning fix.
Adding a new file for distributed local task list for better organization.
Now need to plug back in the distributed termination and work stealing among the cores.
Renamed the Task to TaskQueue, now adding Task class.
Slowly making changes to load-balancing.
Adding the task stealing among cores.
Multicore work stealing should be working.
Some fixes.
Getting there.
Memory leak fix.
There seems to be a deadlock, need to fix in the subtree split part.
Fixing the monochromatic problem.
Another possible bug fix where splitting was requested whenever it hits a subtree that is locked.
OMP critical added.
Some fix. Still debuggin.
Moving the termination check.
Should fix the deadlock.
All fixed, now moving onto load-balancing.
Starting the routing algorithm for distributed dualtree.
Starting the e-cube routing algorithm.
Now have to change the termination condition.
Implementing the routing.
Transitioning.
Fix.
The changes should have fixed the monochromatic problem.
Adding the random seed option.
Fixed so that the rank is fixed after distributed tree building.
Fixing the subtable test to compile.
Taking out parmetis.
Fixed the subtable serialization bug, where the loaded subtable is saved and loaded again, did not result in a valid subtable.
Renaming files.
Remove.
Fixed so that it uses recursive doubling, now need to fix TableExchange.
Recursive doubling scheme started.
Added a method to test the ID of a subtable.
Renaming.
Renaming.
Cmake change.
Compile fix, transitioning to recursive doubling scheme.
Compile fixes.
Fixed so that MPI_Iprobe is done on a smaller neighbor. Now have to fix so that the subtables are coalesced before sending out.
Kind of works, now need to put the asynch barrier only once.
Fix.
Trying to debug.
Fixing in progress.
Patch so that STL vector is not used in all gather.
Formatting.
More bugs fixed, but now have to deal with deadlocks.
Mainly formatting.
Compiling somewhere else.
Fixing now.
Style
Style.
Style.
Debugging
Bug fixed, now have to put back in the termination propagation.
Bug fixed. Now have to fold in the termination condition.
Hopefully the last bug before termination detection.
Style.
Cleaning up and merging termination detection.
Minor change.
CMake change.
Reformatting.
In transition.
Bug fixed.
Default argument revert, since distributed 2-GNP is stable now, now have to do the load-balancing.
Memory leak fix.
Fix.
Removing an obsolete file.
More code cleanup.
Splitting among cores put back on.
Performance bug fix in single node case.
Bug fix in multicore.
Bug fix in getting initial tree frontier.
Temporary patch. Fixing the OpenMP issue.
More cleanup in the OpenMP region.
Table exchange inside distributed task queue.
Bug fix in checking power of two.
Another fix.
Minor tweak. Now going with load-balancing.
Minor format.
Adding a different way of generating dualtree tasks.
Incrementally cleaning up.
Segfault fix.
Compile fix.
Need to fix the STL map problem.
Bug fix.
Added a function to clean up terminated query subtrees so that the searching can be done faster.
Need to put omp_lock inside DistributedDualtreeTaskQueue.
omp_nest_lock_t transition.
Bug fix.
More active task splitting.
Transitioning to the load balancing.
Adding a new data structure that is needed for load balancing.
Getting there to load balancing.
Getting there by implementing subvector class. Now have to implement load balancing.
Update to the MapVector iterator.
Uses MapVector iterator for kde.
Compile fix.
Fixed compilation for distributed tests.
Bug fix.
Adding scoped omp locking.
Getting to load balancing.
Still figuring out how to add load balance.
Compile fix.
Const_cast fix.
Transitioning to load balance.
Getting there.
Optimizing before load balancing, now need to re-prioritize so that the earlier cache is evicted first in the task priority.
More optimization.
Reprioritizing. Now have to implement the rest of the load balancing.
Bug fix.
Another.
Priority change.
Turning off the process rank favor.
Getting there.
Added the option of fixing the random seed.
Easy optimization.
Now the query subtree list is converted to the query subtable list.
Transition to shared_ptr.
Code restructuring for load balancing.
Adding parallel random dataset generator.
Factored out random dataset generator.
Tests now use RandomDatasetGenerator.
Fix.
Taking out boost thread.
Multi-threaded random dataset generator should be working.
Revert since the test is failing.
Fix.
Fix.
Fix.
Test clean up.
Fixed the random dataset generator. Generating weights for kde made series expansion to think that there were actual weights.
More comments before transitioning to load balancing.
More optimization.
Working on map vector.
Getting there.
Getting there.
Getting there.
Tweak.
Getting there.
Transitioning.
Turning off load balancing for safe version.
Load balancing.
Getting there.
Getting there.
Destructor for subtable added.
Fix.
Fix.
Bugs fixed, now continuing with load balancing.
Temporary checkin, still stable version.
Adding copy constructor for kde result.
Copy constructor for local regression result.
Serialization rule for std::pair
Adding flush request.
Getting there, taking a break.
Back to something.
Prints out the elapsed time from the master.
Getting there.
Infinitely closer.
Getting there.
Getting there.
Getting there.
Will continue tomorrow.
Going there.
CUDA kde compile fix.
Minor correction.
Getting there.
Transitioning to boost shared ptr.
Bug fixes.
Plugging in the test mode.
Getting there.
Getting there.
Minor.
Getting there.
Time to finish load balancing.
Adding true parameters.
Going there.
Getting here and there.
Getting there.
Getting there.
Getting there.
More commenting.
Getting there.
Query subtable lock is inside subtables now.
Getting there.
Getting there.
Getting there.
Load balancing added as an option.
Output added.
Bug fixes in task list.
Another bug fix.
Printing out true parameter values.
Segfault fix.
Print out.
Outer iteration added.
Getting there with bug fixes.
Getting there.
Bug fix in core::math::DRange.
Fixing.
Getting there.
Trying to fix load balancing, almost there.
Getting there.
more bug fixes.
Compile fix subtable test.
Changed MapVector class so that it does not use operator[] for find operations.
Adding MapMatrix class.
Getting there.
Hopefully fixes the compile error on no
Getting there.
Compile warning.
Compile warning fix.
Getting there.
Getting there.
Took out core::table::DenseMatrix and core::table::DensesPoint classes and completely replaced with Armadillo.
Memory leak fix in loading of armadillo vector.
Removing MapMatrix.
Segfault fix. Now load-balancing is close to being finished.
Adding the lock toe taskqueue PushNewQueue method.
Bug fixes in TaskList exporting.
Adding OMP locks to distributed task queue methods.
Getting there with load balancing.
Patch for load balance.
Another patch for load balance.
More patches, getting there.
Taking out print.
Print statement.
More prints.
Bug fix.
Another bug fix in MapVector.
Going.
Getting there.
Adding the flag for whether the subtable is being used for query subtable or not.
Getting there, now putting QueryResult inside SubTable class.
Deep changes to allow associating query result with tables.
More patches before finishing load balancing.
Compile fix.
Final compile fix before load balancing.
Another fix.
Compile fix, now load balancing finalizing.
Query result inside query subtable now.
Fixing so that local expansion is initialized for non-empty multipole momenets.
Still debugging.
Bug fixed. Still finishing load balancing.
More optimization.
Converting to intrusive pointers.
Patches to avoid searching through locked query subtables.
Reverting because I broke the code.
Switching to boost::scoped_array
Hopefully I can proceed to load balancing.
Took out print.
Taking out shared_ptrs.
Going.
getting there.
Going here and there, getting to the finish line.
Additional header file.
Fix.
Going again.
Repatch.
Going there.
Going.
More patches.
Almost done with load balancing.
Getting there.
Getting there, now ready to test load balancing.
If a reference subtable comes before the query subtable with the same ID, the task export will forget to save the associated query sub list. Now have to fix so that the reference set and the query set are different.
Still fixing.
Bug fix.
Getting closer.
Almost done with load balancing, still debugging.
Getting there.
Getting there.
Continuing tomorrow.
LockCache method should be called for reference tables stolen from other processes.
Numerous bug fixes in load balancing, getting extremely close to finishing load balancing and start writing.
More edits.
Fixing.
Commit.
Compile fix.
Bug fixes, still trying to get load balancing to work.
New API added to parallel.
Bug fix in ball tree builder.
Basic parallel tree test modified.
Bug fix in the intrusive pointer initialization of reference count.
Moved the SendReceive test outside for distributed dualtree engine.
Taking out print.
Patch for optimizing load-balancing turned off case, roll back three times for a stable version.
Another patch.
Another bug fix.
Another patch.
Bug fixed, now testing stressfully. Just in case, you can roll back about 5 times to get a stable version.
Change to the way points are compared for equality.
API changes to GNP engine.
Final fix.
Another.
Another change.
Fix.
Fixing the monochromatic case.
Will fix the monochromatic problem.
Default thread num
Changed the way is_monochromatic flag is used in the distributed/non-distributed computation.
Fix to the default argument.
Another default argument change to kde.
Default location for gsl changed.
Disabled redistribution of cores on the same machine, now will change the policy of initiating load balancing to reduce the overhead.
Fix to the root CMakeLists to specify the local installation root.
Going.
Added the code to extract prune counts.
Breaking up the file.
Transitioning and cleaning up toward a more efficient load balancer.
Getting there.
Getting there to change load balancing.
Default num thread changed again.
Some bug fixes.
Getting there.
Transitioning to better load balancing scheme.
Getting there.
Commented out task list route for now.
Getting there.
Cleaning up code.
Some optimizations.
Getting there.
Getting there.
Getting there.
Getting there.
More cleanup.
Getting there.
Going.
Plugging back in the load balance.
Getting there.
Changing the termination condition slightly.
Re-do.
Tweak to termination condition.
API change.
API change.
More API changes.
API changes.
API change.
Fix.
More changes.
Fix.
Final change.
Bug fixes.
Distributed/non-distributed two-point tests pass now.
Almost done debugging.
Almost there.
For some reason, uses more memory.
Numerous bug fixes for load balancing, still debugging.
Need to fix the load balancing case, but getting there.
Load balancing works. More stress testing.
Memory leak fix.
Enabled splitting query subtables.
Some minor bug fixes in updating local computation on load balancing case.
Some more optimizations.
Now the flushed query subtables are destroyed.
Distributed kde test now tests load balancing.
Added the branch on tree type in distributed kde code.
Memory leak in load balancing case fixed.
Now dequeues multiple items for slave threads.
Adding the weak scaling measuring mode.
Moved the global all-reduction step of two-point into the two_point_result.h, also finished the weak scaling measuring mode.
Added the static cast.
Another warning fix.
Fix.
Fix.
Some adjustments.
Fixing.
More tweak.
Now need to maybe tweak the load balancing, but the experiment setup should be good to go for weak scaling.
Fix.
Another tweak.
Printing out the initial setup time.
Dividing by the number of threads in the weak scaling.
Distributed tree test compiles now.
Re-enabled the multithreaded tree building.
0.2 to 0.1
Bug-prone disjoint_int_intervals.h eliminated.
Fixing the compile error.
Going.
Added the method to print out global table.
Going.
Going.
Different way of measuring weak scaling.
Bug fix in measuring weak scalability.
Another tweak.
Fix.
Disabled redistribution among cores.
Bug fix in multithreaded tree buildling, now there is a speedup under -O3 flag.
Warning fix.
CUDA fix.
omp_set_nested(false) apparently resets the number of threads.
Need to fix the task division for MPI size = 1, big data case.
Checking in the reference tree walker.
Dualtree iterator bug fix.
Reference tree walker finished. This will save memory by conservatively expanding the reference frontier (which has direct impact on the hashed send list.
Patches for running on a larger distributed computation per node.
Another fix. For a stable version, roll back twice.
Minor.
Changed the seed function.
Leaf size increase.
Another parameter.
Going.
Another patch.
Warning fix.
Warning fix.
Some tweak.
More tweak.
Final change from 400 to 40.
More tweaks.
Patch to encourage sending the reference set as few times as possible.
A tweak.
Another tweak.
One more.
Another.
Another fix.
Compile fix.
More tweak.
Added back the timer.
Some tweak.
Fix.
Another.
Fix.
Now any thread can walk the reference tree.
Added the heuristic for reference tree walk.
Took out print statement.
Some changes clean up.
Fix.
Took out printf.
Fix.
More tweak.
Some changes.
Experimenting now.
Some optimization.
Testing.
Dualtree iterator is slower.
Fixing load balancing.
Some opt.
Fixing the load balancer.
Fix.
Some changes, now need to optimize load balance.
Changed the naming scheme of files in MPI read.
Needs to be fixed by implementing distributed file reader.
More comments, now optimizing MPI calls.
Merged multiple MPI calls into one.
Problem fixed.
Warning fix.
Another.
Another.
Another.
Another.
Going.
Fix.
Fix.
Fix.
Suffix fix.
Some changes so that messages can be buffered more quickly.
Revert.
Bug fix.
Fix.
Transitioning to compact buffering.
Now subtable routes can go faster.
Fix.
Fix.
More optimizations.
Merged.
Reverting.
Going.
Patch for extrinsic prune.
Patch for more balanced splits in the global tree in distributed tree building.
Formatting.
Tree test compile fix.
New argument to specify attribute dimensions for full Gaussian.
Fixing the Gaussian distribution.
Now debugging.
Terminates when --attribute_dimensions_in missing for full Gaussian.
Fixing the test.
Change so that SamplingAccumulatePrecompute is called automatically everytime beta is drawn from the distribution.
Option to simplify outputs.
Adding a random generator for DCM Table.
Random parameter generation.
Garry Boyer (339):
create
Added basic directories.
library in
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added comments so doxygen will pick up trees
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Updated to support external tree
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latex help for matrices
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use curl instead of wget
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works with spaces
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fixed help for fx-cleanup
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linear svm seems to be working
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Fixed the damn bug
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looks like superpar will be taking life soon
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tkde expressed in GNP-preduce -- yay
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fixed a build system problem
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Holy Object Traversal BATMAN!
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Removed backup files
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TKDE WORKS!
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fixed my bugs
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64-bit building
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fixed bug in fastexec with integer reading
build system slight update
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Added affinity and other algorithms
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Added utils directory
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Added a section 2
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made stuff smaller, added aff
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Updated AP
Made figure 1 work
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added intmap
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okay, finding minor design problems, i'll check back in later
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woot, parallel works on one machine
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ITS ALIVE!!!!!
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close to working now
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working nbr
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thor moved into the main line -- tree code experiences radical changes
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improved alignment issues
Please do not add temporary files to Subversion
added allnn
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more thor stuff
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more updates to thor -- sorry
separated out interface from implementation
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cleaning up documentation
documentation fixes
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fixed a compile issue with thor
parallel works again
made affinity converge better
affinity converges again
affinity converges again
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oops, fixed a bug
moment expansion works, apparently
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added index to thor
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made some fixes to thor's file access
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fixed a bug
non-portable mutex initializers no longer used
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separated dfs.h into dfs_impl.h
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added some metrics to thor, fixed my kde to allow gaussian convolution
fx-rpc now works with fx
breadth-first seems operational
gdb support for fx-rpc
slightly improved breadth-first
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paper modifications
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added ball tree bounding structure
fixed tree bug
rolled back Doxyfile
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DO NOT CHECK IN LARGE FILES
allow use of gfortran
committed
Making q_mutables slightly better.
Grzegorz Krajewski (8):
Add note about runtime_error exception
Add test for twice start/stop timer
Add changes for runtime_error exception.
Throw a runtime_error exception for start/stop
Change contributors list
Add getter for timerState.
Definition of GetState().
Terminate the program timers.
HurricaneTong (24):
initialize tree pointer
add pooling rules
add two layers
add pooling connection for CNN
xcode
Revert "xcode"
implement mean shift algorithm
support for selecting kernel
delete unused header file
template order
Add test case
estimation of duplicate thresh
optimization
add metric
zero duplicate thresh test
make test in correct order
only consider points within radius
implement Gradient()
use SquaredEuclideanDistance
remove unnecessary kernel traits
use unsafe_col to speed up
generate seeds as initial centroids to speed up
involve mean to calculate new centroid
delete obsolete paramater
James Cline (118):
Create fastlib-vector branch for swapping ArrayList -> std::vector.
Converted rangeset.h to use std::vector. Needs testing, still.
Switched MinHeap to use std::vector.
Sped up slightly. "Safer" code.
Switched from ArrayList->std::vector.
TestRangeSet() changed so that it actually will fail if the expected results are not generated.
Fixed TestQueue so that it actually fails if things don't match.
Forgot to change this back before previous commit.
Queue is now just a wrapper around std::deque. It will be completely removed later on as the things that call it are updated.
Updated comments. Removed constructor nonsense.
Rename branch to indicate its new purpose, switching from in house implementations of things in the standard library to the standard library implementations.
Queue deprecated and removed. std::deque should be used now instead.
Remove ArrayList and String. This commit breaks many other classes.
Reimplemented String's tokenizer for std::string.
More things that compile yet remain untested.
More untested yet compilable files.
cmake target fastlib compiles, as do several of the tests before cmake gets to mlpack.
fastlib/thor compiles now, except for allnn.cc.
More stuff compiles, all untested for correctness.
Fixed tokenizer bug. Added a hopefully finished unit test for the tokenizer.
Removed error checking for converting numbers to strings when unecessary.
Removed useless Init method in rangset.h.
Removed unecessary #include.
It was dumb to not have done it this way to begin with.
The textfile_test now passes.
Passes its test now.
A couple comment updates to reflect ArrayList -> std::vector change
Added some bounds checking
Incorrect matrix access via [] instead of (x,y).
Fixed memory leak.
Works for svm_c learner, linear or gaussian kernels for training and testing.
The svm_r learner now "works" for linear and gaussian kernels for training and testing.
Make parameter passing to SMO::InitPara sane.
Switched over kernel_pca stuff to use arma & std.
assert() undefined, added #include <assert.h>
naive_bayes compiles now. Currently untested. Could also possibly use some cleaning up still.
Works correctly now, just need to get the output to be in csv format.
Uses data::Save to save as a CSV file
Nothing in this file is used anymore.
Converted to stl stuff, still some bugs
Cleaned up and optimized naive_bayes a bit.
Added the option to enable or disable bounds checking in armadillo for fastlib-stl.
TEST_DOUBLE_APPROX failed when at least one of the numbers was NaN.
Comment updates, unit test, and optimization
Should be up to date, now.
Compilation error, ptrdiff_t not defined, add #include <cstddef>
Found another ptrdiff_t problem, added #include <cstddef>
const IO::IO& other didn't compile with g++ 4.6
g++ 4.6 wants #include <cstddef> when using things like ptrdiff_t
Fixed some missing IO parameters for SVM and incorrect types.
It helps to attach the new file..highlight.
Ticket #54 and a bit of refactoring.
Create a simple linear regression class
error: ‘struct arma::subview_col<double>’ has no member named ‘ones’ fix
LinearRegression -> mlpack::linear_regression namespace
formatting changes
fastica -> mlpack::fastica, lin regr style
hmm methods -> mlpack::hmm
infomax_ica -> mlpack::infomax_ica namespace
naive_bayes -> mlpack::naive_bayes namespace
regression -> mlpack::regression namespace
Make main usable, --help explains options now
nnsvm -> mlpack::nnsvm namespace
helps to add the files
Make lin_reg adhere to the proposed interface for mlpack methods.
Put dballbound into namespace mlpack::bound
mlpack::math namespace mess
Remove using namespace mlpack::math in favor of math::Range
Change core/tree, core/math to *.hpp, *.cpp
change optimizers/* to use hpp and cpp file extensions
Change core/model to use *hpp, *cpp
Change linear_regression file names to hpp, cpp
Move nnsvm to *hpp, *cpp files.
Move emst to hpp, cpp extensions
Move fastica -> hpp, cpp file extensions
Rename files to .hpp, .cpp
Add load and save and a constructor that loads model from file
Fix #ifndef, #define, #endif
Fix braces, #153
mog/* to hpp & cpp filenames, fix #defines, etc
core/file to hpp & cpp
comments
Linear regression changes & fixes
Better comments, coding style improvements
Fix all the things cppcheck didn't like.
We don't actually need a reference to the new child...
non-class type return values are non-modifiable, const qualifier is ignored (-Wignored-qualifiers)
Comment out unused parameter names (suprisingly valid C++), -Wunused-parameter
How many unused parameters does one library need...
Fix the compilation error from my -Wunused-parameter fix when compiling
Another -Wunused-parameter fix
Add -Wextra and -Werror for debug and non-debug builds.
Apparently jenkins uses an older version of boost and we had a #define that
The parameter names were... wrong.
Default and copy constructors.
This fixes the arm test bug.
Various improvements to LinearRegression and our executable.
Incomplete rough draft of the LinearRegression tutorial.
coding with LinearRegression examples
more comments for the comment god
fix ticket #184
MRKDStatistic for mrkd-trees. Probably still needs improvements.
Make this actually compile when used with BinarySpaceTree
Appears to work now.
Add a splitDimension variable and getter for determining which dimension a node is split on.
Tab fix (think I got them all)
fabs(max(,)) -> max(fabs(),fabs())
Mostly, hopefully, working implementation of Pelleg and Moore's mrkd tree k-means.
Something's wrong with this
Working, mostly finished pelleg and moore mrkd kmeans implementation
Add more fields to the mrkd statistic
comment fix
Forgot to commit this, fixes forgetting to set minDistance
Update metrics to support distinct vector types as arguments.
remove useless code
Switch from armadillo's load() to data::Load()
Fix tabs
Fix test compile time errors, missing <> for GMM
Janzen Brewer (3):
Add OpenMP support to density estimation tree code
Optimize small things in density estimation trees
Replace unsupported array operation with arma::vec
Jaskaran Singh (4):
.so problem fixed
.so problem fixed
.so problem fixed
Updated path of install in Readme
Marcus Edel (294):
test commit
Removing "test.txt"
Fix ambiguous math reference error, to pass the test on OS X with clang.
Add target_link_libraries for librt to support clock_gettime() for Linux.
Update the timer class, to get stable time values with more accuracy for the common operating systems.
Remove unnecessary include.
Fix ambiguous math reference error, to pass the test on OS X with clang.
Fix ambiguous match: option -s matches --seed and --single_mode.
Fix index out of bounds error when using det with a labels file.
Fix ambiguous match: option -s matches --single and --scale.
Fix ambiguous matches for -N and -L and set default optimzer sgd.
Fix ambiguous call to pow, to pass the test with clang.
Fix ambiguous match: option -d matches --degree and --new_dimensionality.
Add opportunity to set initial centroids.
Add command line option to set initial centroids.
Fix typo that breaks kmeans.
Ignore the cover_tree option if the naive option is present.
Improve centering of the kernel matrix.
Use the correct option to output the desity estimates.
Fix ambiguous match: option -p matches --in_place and --percentage.
Use the option to set the leaf class table file and unify method call.
Update the timer example call and output.
Fix ambiguous call to RandomSeed, to pass the test with clang.
Check the matrix dimension before dropping unnecessary rows.
Fix typo: furthest <-> nearest.
Save the correct labels; thanks Anand!
Assume the response to be the last column of the input file, as pointed out in the description.
Fix ambiguous math reference error, to pass the test clang.
Don't save a rowvector into a colvector. Use the build in option of the save function to transpose the vector.
Add nystroem method for kernel approximation.
Add test for the nystroem method.
Embedding nystroem method into kernel pca method.
Outsource the matrix multipilcation.
Avoid direct multiplication with a diagmat.
Integrate nystroem method into the kernel_pca_main.cpp file.
Improved nystroem localisation ('oe')
Fix normalization bug (transpose); Some more comments.
Center the reconstructed approximation and the kernel matrix.
Scale the transformed data matrix.
Use the maxIterartion as template parameter.
Handle variance calculation with zero eigenvalues.
Remove unnecessary include directives.
Right now, we can't load a vector, so we load a matrix and extract the last column.
Add maxIterations parameter to limit the number of iterations used in the Newton method.
Fix ambiguous math reference error, to pass the test clang.
Make size_t known before including cxxabi.h to fix the build on FreeBSD.
Add build status badge.
Add implementation of identity activation function.
Add implementation of logisitc activation function.
Add implementation of the rectifier activation function.
Add implementation of the softsign activation function.
Add implementation of the tanh activation function.
Add connection traits class.
Add implementation of the full connection class.
Add implementation of the self connection class.
Add implementation of the random weight initialization method.
Add implementation of the Nguyen-Widrow weight initialization method.
Add implementation of the optimal initial value setting initialization method.
Add implementation of the weight initialization method by T. Kathirvalavakumar and S. Subavathi.
Add implementation of a feedforward network container class.
Add implementation of the iRPROP- method to update the weights.
Add implementation of the iRPROP+ method to update the weights.
Add implementation of the RPROP- method to update the weights.
Add implementation of the RPROP+ method to update the weights.
Add implementation of the steepest descent method to update the weights.
Add implementation of the LayerTraits class.
Add implementation of the BiasLayer class.
Add implementation of the orthogonal initialization method.
Add implementation of the NeuronLayer class which can be used as basic network layer.
Add implementation of the MulticlassClassificationLayer class.
Add implementation of a recurrent network container class.
Minor comment fix.
Add implementation of the LSTMLayer class.
Add implementation of the SoftmaxLayer class.
Add implementation of the cross-entropy error performance function.
Add implementation of the mean squared error performance function.
Add implementation of the sum squared error performance function.
Add activation functions test.
Add connection and layer traits test.
Add test for the init rules.
Always get the boolean value and store it in a temporary, because the Boost unit test macros do weird things and will cause bizarre problems.
Add performance function test.
Add network traits class.
Store the gradients to allow batch learning.
Initialize the gradient storage with zero.
Remove the input parameter since we can't provide an input for batch learning and it wasn't used anyway.
Updated link to download the latest version.
Add Trainer class which serves as container to train the networks.
Return a number in the interval [0, 1] instead of [0, std::numeric_limits<eT>::max()].
Minor style change.
Add test cases for the feed forward network.
Remove unused test case.
Add binary classification layer.
No need to change the sign afterwards.
Take a mean gradient step over the batchsize.
Basically you don't need to shuffel the input in batch mode; However at least there is the option now.
Add the ability to define the training parameters.
Slightly adjust the number of neurons to decrease the runtime.
The connection type defines how to multiply the input activation and the delta.
Use Gradient() to get the gradient.
Set a default value for the seqnumer.
Use the correct input to accumulate the elements. Thanks to Shangtong for pointing this out.
Minor style fixes.
Add function to evaluate the network.
Use the correct number of epochs.
Properly handle the rnn structure.
Add test cases for the recurrent neural network.
Merge branch from github.com:zoq/mlpack to address structure issues.
Minor style changes.
Adjust the rnn class and LSTM layer to handle sequences of different lengths.
Add embedded Reber Grammar test to test the LSTM layer.
Inplace gradient calculation for peephole connections.
The class template auto_ptr is deprecated, use std::unique_ptr instead.
Add test case for the LSTM peephole connections.
Add distracted sequence recall test (LSTM architecture).
Minor style changes.
Add support for 3rd order tensors as input to train neural networks.
Add function to get the number of cols/slices. Thanks Shangtong for pointing this out.
Adapted Shangtongs naming schema to distingush between layer and connections.
FindPackageHandleStandardArgs.cmake ships with CMake from version 2.8 onwards, since we require CMake 2.8.5 delete the outdated copy.
Using backtrace() become somewhat tricky when going multi-platform. Use CMake to figure out the correct header and library.
Minor cleanup of double header inclusion and file comments.
Add simple Log::Assert test case.
I was not going to revert the last commit.
Avoid generation of the backtrace.hpp entirely.
Minor cleanup (svn -> git transition).
Explicitly include the CreateGitVersionHeader module.
Minor cleanup of the local coordinate coding test;
Link against libc++ when using clang on OSX.
Use CMake to figure out if we need to link against libc++ or libstdc++.
The compiler should automatically select the right stdlib on most systems.
Minor cleanup (tutorials link, git commit mailing list link).
Highlight some commands.
Add implementation of convolution using the naive approach (it's pretty fast for small filter).
Add implementation of convolution through fft.
Add border modes (valid convolution, full convolution).
Add implementation of convolution using svd to speeded up the computation.
Add 3rd order tensors support (convolution).
A test for convolution algorithms.
Merge pull request #433 from HurricaneTong/pooling_rule
Add comments, and minor cleanup.
A test for the pooling methods.
Return MatType instead of arma::mat.
Merge pull request #434 from HurricaneTong/latest
Add convolution batch mode.
Add test case for the convolution batch mode.
Add 3rd order tensors support (weight init methods).
Adjust weight init methods.
Merge pull request #435 from HurricaneTong/cnn_pool_connection
Merge pull request #436 from HurricaneTong/add-cnn-network
Rename pooling connection.
Swap naming convention.
Minor style fix.
Clean the steepest descent optimizer class and add tensor support.
Adapt new design pattern.
Add new connection trait.
Fix ambiguous constructor.
Refactor pooling connection to support 3rd order tensors.
Style overhaul, and clarify some comments.
Rename the conv connection class.
Refactor conv connection to support 3rd order tensors.
Add method to get the number of slices.
Refactor neuron layer class to support 3rd order tensors.
Add the convolution neural network to the network traits.
Refactor the convolutional neural network class, it's almost idenical with the ffnn code, but we add more features in the future, so copy the code right away.
Add convenience typedefs: ConvLayer, PoolingLayer.
Handle 3rd tensors, when calculating the first derivatives of the identity function.
Fix the include guards to avoid the problem of double inclusion.
Don't make OpenMP a requirement to build the source.
Simplify the usage of the performance function by reducing the template parameter.
Use the simplified performance function.
Adjust the performance function test; use the simplified performance function.
Refactor to support convolutional neural networks.
Slight refactorization for simplicity. No need to specify additional template parameter.
Refactor the bias-, softmax- and lstm-layer to pass the convolutional neural network change.
Populate the matrix with the entries of the max value.
Make sure we calculate the correct delta when using convolutional neural network.
Add batch support. In batch mode, the convolution runs on a batch of images.
Reset the delta before calling the unsampling method.
Use the rotated filter to calculate the delta.
Refactor to support 3rd order tensors.
Use the number of rows and cols to initialize the optimizer.
Add a test for the convolutional neural network.
Fix unused parameter warning.
Oops, use the right test file.
The gradient to update the weight depends on the number of output maps.
Fix typo and minor style change.
Add bias connection, that works with convolutional neural networks.
Use bias connection and decrease number of epochs.
Fix typo.
Add RmsProp optimizer.
Fix typo.
Use RmsProp and decrease the number of epochs.
Add function to update/reset the optimizer object.
Use the new optimizer interface.
Adjust connections; use new optimzer.
Refactor for new optimizer API.
Use the complete dataset.
Use MaxPooling as default pooling rule.
Refactor for new optimizer API.
Add update formula.
Fix the name of the input parameter.
Add Adadelta optimizer.
Refactor to support 3rd-order tensors.
Make the layer independent regarding the datatype.
Add dropout layer; regularizer that randomly sets units to zero.
Add identity connection.
Add weight zero initialization rule.
Rescale the input unless the user explicitly requested not to.
Add new connection trait (identity connection).
Update the connection trait and there is no need to reset the delta, we already reset the delta in the network class (cnn, ffn).
Update the all connection traits; including the self and fullself connection.
Use the naive convolution method as default.
Handle the identity connection.
Avoid overflow by subtracting the maximum of the input values from each input.
Gradient calculation speedup by iterating over the output maps.
Use the rectifier function for the whole test and decrease the overall error tolerance.
Set the current evaluation mode.
Add convolutional neural network dropout test.
Add feedforward neural network dropout test.
No need to specify the size of the delta parameter.
Simplify the training process.
Set the correct evaluation mode.
Add deterministic parameter to distinguish between trainign and testing.
Handle the identity connection.
Minor misspelling fix.
No need to specify the type of the input data.
Add function to get the current gradient.
Refactor for new multiclass output layer.
Add convenience template typedefs to the CMakeLists.
Minor misspelling fix (use 'Optimizer' instead of 'Optimzer').
Include the connection traits.
Refactor test for the network API.
Build the activation functions.
Add linear layer.
Add base layer.
Minor style fix (80 character limit).
Minor misspelling fix.
Refactor for new network API.
Refactor feedforward network test for new network API.
Replacement for the FFNN class using the new network API.
Refactor to handle 3rd order tensors correctly.
Add SFINAE pattern for the Gradient and Deterministic function.
Refactor bias layer for new network API.
Replacement for the convolution connection class using the new network API.
Refactor to handle 3rd order tensors correctly.
Minor misspelling and style fix.
Update Layer traits for the multiclass classification layer.
Updated layer traits (binary classification layer and one hot layer).
Replacement for the pooling connection class using the new network API.
Decrease the overall test time by decreasing the layer size and number of epochs.
Distinguish between OutputParameter and InputParamater.
Refactor dropout layer for new network API.
Remove the no longer needed connections.
Refactor feedforward network test for new network API.
Add CMake files to build and test the activation functions.
Remove subfolders from the CMake file that doesn't contain a CMakeLists.txt file.
The transform() function isn't available on armadillo 3.6 so we move back to a standard for loop.
The transform() function isn't available on armadillo 3.6 so we move back to a standard for loop.
Refactor all activation functions and layer which uses the transform() function.
Comment out the ann code.
Use at least armadillo 4.x to build mlpack.
Add travis ubuntu trusty repository.
Refactor softmax layer for new network API.
Use the correct filter/kernel parameter.
Provide a few convenience typedefs.
Build the neural network code.
Limit training epochs and add thyroid dataset.
Decrease the overall test time by decreasing the layer size and number of epochs.
Widen tolerance for the network decreasing error test.
Remove unused layer and optimizer classes.
Remove unused header.
Refactor convolutional network test for new network API.
Refactor convolutional network main class for new network API.
Use mean pooling as default pooling rule.
Refactor optimizer for new network API.
Remove unused function; we only need to support 3rd-order tensors.
Add 3rd-order tensor support (Dropout layer).
Use the filter matrix for the convolution function instead of the 3rd-order tensor.
Build the convolutional neural network code.
Widen convolutional test tolerance.
Comment out the convolution test.
Use the logistic function and the RMSProp optimizer because the combination tends to be more stable and in most cases it converges faster using the specified architecture.
Fix 'no known conversion from arma::Mat<double> to arma::Cube<double>' error that occurred on some systems. Actually the build should be fine even without the change, but I guess some systems like to draw our attention on some 'incredibly long' templates in the error log.
Use static weights for the network decreasing error test.
Build the convolution test.
Merge pull request #459 from stereomatchingkiss/ann_workaround
Minor syntax and formatting changes.
Minor documentation updates and formatting changes.
Add ADAM optimizer.
Add a test for RMSProp.
Use the correct number of feature maps in the network description (thanks Ngap wei Tham for pointing it out).
Merge pull request #462 from stereomatchingkiss/FixOIVSInitBug
Merge pull request #463 from stereomatchingkiss/FixDropOutLayer
Matthew Amidon (82):
Added io.cc and optionhierarchy.cc
Fleshed out IO interface, integrated OptionsHierarchy into IO.
IO is functionally complete. Will begin integrating with the rest of the library upon discussing a few particulars with Ryan.
Added io_test.cc to the repository.
Edited in timer support to IO. The timers work, in the middle of integrating timer support with globalValues.
Implemented timers, should probably implement a method of printing certain values to console. That should basically be it fofr IO.
Cleaned up IO, began phasing IO into allKnn. Also took a look at WITH_SPARSE=ON bug. (No solution yet)
commit 5e745f3f5943272e531c3d69e1192795e45fa1c5
Finished integrating IO into AllkNN, AllNN. TODO, figure out SPARSE issue, continue integration, work out what Ryan wants as far as Output is concerned.
Started working on template magic to make easy parameter registration. Don't use these just yet.
Working on the output portion of IO. Finished the registration at compile time feature.
Continued work on IO output. Added system for automatically printing output without further programmer interaction. Working on formatting output.
Going to refactor optionshierarchy, it's basically not extensible. Also, IO seems to not like having singleton declared as a non pointer type;
Finished auto-output for int, bool, string, and timeval types. Adding more types will be trivial.
Cleaned up io source, got trolled by ryan and left camel case.
Cleaned up code to better conform to standards, edited vim configs to help out
Fixed a bug in IO. Replaced FX functionality in allnn/* with IO functionality
Fixed a few bugs, still working on one in IO::PrintAll
Added formatted comments, will add them to cc files after unit tests are finised
Unbreaking the build server.
Finished unit tests, finishing up documentation in the cc files,
Did some more cleaning. Working on making output streams more robust.
Implemented output to specifications. (Re)implemented debug output/null output
Fixed that bug.. gotta watch those references.
Resolved ticket #75 by retyping leaf_size and 'k' as ints. Modified io unit
Removed unused code. Refactored some methods in IO. Fixed allnn into
Began implementing IO in mlpack's emst and fastica methods.
Replaced FX with IO in HMM, Kalman, and Infomax today. Worked on some IO stuff, which will require more thought.
Modified PrefixedOutputStream's behoviour (sp?).
Resolved a bunch of tickets. Renamed GetValue and CheckValue to HasParam and GetParam. Also modified the behavior for flags.
Went through all the files in kde and replaced fx with IO. I will need to go though them again and make sure
Finished cleaning up KDE. Apparently KDE is not currently part of the build process;
Integrated IO for the remaining parts of mlpack. Will go through and make sure nothing's been missed.
SVN crapped out on me, rechecked out blah blah blah.
Reverted change to io_test. I think I was killing the server by printing
Fixed a bug, where options like '--help' and '--info' would
Reverted part of IO's default modules logic.
Implemented default modules, hidden Info except on verbose. Working on
Fixed a potential bug where documentation would be overwritten
Replaced various macros etc in cc.h that were used sparingly.
Apparently I deleted that from svn too soon.
Reverted cc.h deletion, added in includes for STL files algorithm and limits.
Resolved ticket 93, deleted debug.c & debug.h
Fixed a test case that was failing in matrix.h
Removed dependencies on base.h, replaced with common.h
Actually deleted cc.h
Removed most everything from common.h, deleted common.c;
Removed success_t, replaced with boolean logic.
Actually deleted base, minor modifications elsewhere.
Implemented windows based IO timers, will need to actually compile/run on a
Fixed a bug where flags received a default value, which resulted in HasParam
io_test depended on earlier behavior for default values & flags. Fixed.
IO HasParam/GetParam for bool is solved. Both will now reflect the actual
Replacing tree_test, at a good stopping point.
Merged kd tree test with tree test itself. Didn't see the point in adding
Performance improvements to kd_tree_test, added peer bounds checking.
Removed some output's that will break the automated unit tests.
Reduced the size of the kd_tree_test again, that way it will *hopefully*
Split IO into IO & Log. Fixed everything up, all tests work.
For some reason it seems Sed missed gmm and it was already up to date so
Split timer functionality from CLI to Timers.
Reformatted #includes according to new specifications.
Fighting with SVN over actually committing changes for timers.
Formatted according to new brace styles.
Fixed regression w/ timers.
dd
Checkin mid-progress. Arbitrary data types added, need to clean up
What is wrong w/ my svn?
Working copy SVN metadata is broken..
Diffed a clean working copy, this should end my svn issues.
Reverted changes, as it is apparent diff did not work. Will work on that, too.
Fixed some formatting.
Ripped CLI out of nbc & gmm. Moved over to their respective mains.
Ripped optionshierarchy out of CLI, deleted files.
Reimplemented CLI w/o heirarchy.
Did some more formatting of output.
Did some refactoring on CLI, fixed a potential bug.
Implemented range search, need to implement output functionality.
Removed c-strings in favor of std strings.
Modified string types in cli & related sources.
Added enhancements to pca & kernel pca.
Modified PCA/Kernel PCA interfaces to remove redundant centering option.
Nikita Araslanov (1):
kmeans: small fix with inf variance
Parikshit Ram (201):
first upload of nbc
removed the small error and added again
this is the first version of EM uploaded
this is the first upload of the mog_l2e, the file l2_error.h still needs some modifications
these files are cleaned up a little bit but still to be commented
The files have been commented and a README file has been included for assistance
Comments added properly to all the files except phi.h and math_functions.h
the commented files as well as a README file
the README file
added author name
Required changes made and author name added
program changed as per ryan's review and author names added
the set functions added to mog.h
adding the proper set functions in mog.h
the program will now spit out the likelihood value of the model chosen and the model parameters too
Destructors removed
edited as per ravi's comments and added fastexec magic
changes made as per ravi's suggestion and added fastexec magic
README modified as per parameters changed in the previous commit
README modified as per parameters changed in the previous commit
minor modifications made regarding results and fixing the D param in the submodule
required changes made, optimizer class defiined and used, fx magic included, math_functions.h removed, 01/23 at 4:42
math_functions.h indented properly
phi.h documented properly
phi.h documented properly
phi.h documented properly and README.txt changed slightly
author name added
author name added
minor comment mod
minor comment mod
minor comment mod
slight chance made
test class header file deleted
optimizer added to svn, forgot it earlier
l2_error.h removed
small dateset added
README file edited for date file
small dateset included and README changed accordingly
optimizer added separately
optimizers.h moved to opt and removed from here and README edited accordingly
test file removed
test file corrected and added
s_min value increased to remove floating point underflow
polytope had a sign mistake which was removed and corrected
optimizers.h updated
mog.h updated
using the new repository as of now
this code is to be optimized and made faster
the code is to be optimized
corrected stuff working
corrected version updated
faster folders removed
gradient descent added
SGD and SMD_single step implemented but some problem with SMDSS
different terminating conditions included
optimizers added with more terminating conditions although none seem to work, and main deleted accidentally
optimizers tried with mu > 1 but exploded so reduced it so i dont know exactly whats the change in optimizers.h, but the main.cc is added to the svn
covertrees folder added
fkdnfl
Cover tree files uploaded, tree building coded up, not working, still waiting on dependencies of ArrayList
testing files added to svn
files added but not compiled as yet
nearest neighbor preliminary code complete and working on a small test dataset
nearest neighbor preliminary code complete and working on a small test dataset and output decent
Small bug in warning message corrected, no functionality changed
tried to make it faster, but didn't help too much
trying a new thing so saving stuff in the svn
distances changed and exptl folder added
SMD multi step added with fast Hv product in main
updating main and optimizers_reloaded.h
ctree.h corrected, self_first added and Is_leaf function added
depth first and brute added
comments added and files made shorter and hence more files added
small changes made
fx-param stuff put in to get rid of the warnings regarding documentation
minor changes in allknn_impl.h and distances.h
gonzalez file added and other files commented
all gonzalez stuff uploaded for trying to fix gonzalez, make it fast and accurate
stuff removed
sparsepca and lle added so as to get ready for the fastlib 0.2 release
conflicts resolved
fx documentation added
fx documentation added
fx documentation added
fx documentation added
fx type fixes
fx type fixes for mog_l2e
fx type fixes for opt
opt path changed to mlpack/ and build file changed accordingly
mog_em and mog_l2e directories merged to form mog and opt directory renamed optimization and parm_nbc renamed naive_bayes
useless files removed
optimizer path corrected in mog/mog_l2e_main.cc
merger of mog completed and the naive_bayes README changed
approximate rank nn added
approx_nn.h delete function corrected
approx_nn.h modified from home
approx_nn.h completed, main.cc modified for testing
all files completed - testing and debugging ensues
main file contains error message for lapack
init running and test datasets added
ComputeProbability_ fixed and main and approx_nn.h Init functions working
nn algorithm working and exact and naive match
fast uplod
approx nn running, need to check its correctness
need to fix the way I compute node size and also why it is not faster for higher error probability
randomization added but still not figured out certain problems
dual tree traversal added and certain other changed made, like trying exact before sampling, but haven't tested it yet
dual tree traversal added and randompermute replaced by RandInt and various other modifications made
main file added to drive the dual tree version
final tested version with dual tree behaving weirdly
corrected for dual tree and tested, timings testing not done yet
optimizers.h and .cc moved to mog directory from optimizers directory
approx nn single and dual tree fixed up and experimented with.
rank error and distance error computation included
rank error and error probability computation added in main_dual.cc and comments added to approx_nn_dual.h
checks added to see if sampling is done properly
one check fixed
bounds fixed and main_dual changed a bit
default values of doexact and doapprox changed to false
outputting results added to main_dual.cc, but only problem is that if you do multiple methods together, all results come in together in the same file
main_dual printing results option added
empty density tree directory added
the dtree.h file added for the first time
dtree.h updated
main.cc and build.py added and dtree.h updated
main.cc and dtree.h updated
ComputeValue function added in dtree.h
crossvalidation and tree drawing added
everything works as expected just that it is overfitting
changes added to enforce minimum leaf size, other comments added. But idea is that once this works, continue testing with it, while I change the code to deal with nominal data later
MIN_LEAF_SIZE removed and not testing on huge datasets which is taking forever
dtree.h and main.cc changed for diettrich
NoConstraints tests added for all Methods
Box constraints, Linear Equality and Linear Inequality added to Objective function class along with a skeleton for future work
Testing BoxConstraints, Linear Equality/Inequality using LBFGS
some changes made to the test file and it is added to the build file
gonzalez tree removed for now and just plain old covertree tested here
rank-approximate NN files added to new branch
making appropriate changes (hopefully) to the CMakeLists
updating files for dtree without updating the CMakeLists
Aug 9, 2011 - mmtrees code added
Maximum inner product search added
CMakes added
invalid declarator error
max_ip_main compiling
Post bound fix and correct answer, then svn update and all-fail
angle-prune added - not tested yet
Max-inner-product single tree code working fine with and without angle-pruning
Cosine tree essentials implemented -- not compiled yet
cosine cone bounds cleaned up and completed -- pre-compiled
cosine tree example + compiled and lightly tested cosine tree bounds and distances
Dual-tree max-ip implemented but not yet compiled because of weird CMake error -- will wait till later to figure out
Still not compiling - some linking error where the .cc file is not getting linked. Can't figure out what I am doing wrong with the CMakeLists.txt
CMakeLists.txt edited to include mlpack_contrib
sep 22, 10.40am
Sep 23, 2011 update -- header guards added
Sep 23, 2011 update -- header guards added
Dual-tree max ip search implemented and compiled, not tested yet
Dual-tree max ip search implemented and compiled, not tested yet
Dual-tree max-ip-search still not working
Dual-tree code tested, not correct with angle_prune yet
Max-IP search: dual-tree angle-prune tested and working on toy dataset
Sep 29 update -- everything works, graphing script added
The WarmInit() function in class MaxIP fixed to reset the QueryStat in the query-trees, and the tester changed to compute naive only when you have to check for correctness
data_grapher.pl fixed to align to the correct column
data_grapher.pl fixed to align to the correct column
assert in exact_max_ip.cc fixed to either expect 0.0 with -1
MaxIP search ported to new MLPACK and ComputeBaseCase is modified to use memmove instead of vector and push_back
Rank-Approx MaxIP partially completed and not compiled yet
Oct 20 arma error
alt traversal implemented and checked, approx-max-ip still to be checked
Approx max ip running, approx tester running as well (but both not thoroughly checked
Approx max ip running, approx tester running as well (but both not thoroughly checked
Oct 25th, Rank-approximate fixed for very high k-values
appropriate changes made to work with new mlpack + alt-angle-pruning added
Waiting for arma::load() transpose -- quick fix now
Cone-tree code named appropriately
Cosine tree -- co-axial cone tree added and tested
MaxIP search commit after submission, need to clean up code and add approxMaxIP and fix the dual tree
New pairwise distance computer
fixed some stupid typecasting warnings
Density Estimation Trees (DET) added to mlpack
DET CMakeLists added
DET CMakeLists
DET naming schemes
DET naming schemes
DET Tests (almost all done) added
DET tutorial 1st draft
RandInt() and Random() sped up by just using randomUniformDist
LSH class updated: Hash width computation moved within the class and removed from the main file. More comments added to the LSH class. Search function made tunable allowing the user to chose the number of hash table he/she choses to search in.
RANN moved into trunk from contrib/pram. Test added to the mlpack/tests/ directory along with relevant datasets
test data loading fixed
LSH Test modified
minor update to remove some warning for the pow() function
minor update to remove some warning for the pow() function
LSHSearch class MetricType template removed and only metric::SquareEuclideanDistance used appropriately throughout the class
'force_inline' added to ra_search_rules_impl.hpp
Ticket #293 initial fix -- review waiting.
Chebyshev distance (L-infinity distance) added to lmetric.hpp
LBFGS test compilation failure fixed
metric_test.cpp -- arma::sum changed to arma::accu; LINFMetricTest corrected.
Pavel (1):
Fix classification error
Qiang Kou (1):
fix #449
Ryan Cirtin (2):
Fix typo/bug and memory leak.
Initialize variables more nicely.
Ryan Curtin (3395):
Opt++ should not be enabled by default
The use of cmake deprecates and prompts the removal of the entire old build
As per Sooraj's request, tylesBase is no longer necessary and has been removed.
Move 'fastlib' to 'fastlib-old' repository
Add fastlib directory structure
Move fastlib2 to fastlib/trunk
fastlib2 directory is no longer necessary and is thus removed
Move fastlib-old (originally 'fastlib') to fastlib/branches/fastlib-old where it
Move fastlib3 to a branch of fastlib
Move cmake branch into fastlib branches
Remove empty proposals directory
Don't need this structure inside of this branch
Move things in trunk/ to here (incorrect branch structure)
Unnecessary nonstandard directory, if necessary, should be generated by build system
Should be generated by build system at compile time and not in source repo
Unnecessary directories that should be generated at compile time (missed these on the last revision)
Move fastlib directory to src (this will eventually be done in trunk/ once this is merged)
Do not autogenerate this file, no need to reinvent the wheel
No need for this anymore
config subdirectory is no longer needed as basic_types.h is no longer generated
Clean up trilinos search (use PATH_SUFFIXES), and we also need to look for MPI headers.
Update include locations
Update all #includes. From:
Missed this file: changed #include "fastlib/..." to #include "..."
Remove unnecessary debug output, forgot to do that before checkin
ctags cruft shouldn't be in repo, was probably put there by accident
Do not use different directories for cmake stuff; this ensures every directory has its own Makefile.
Oops, this should not be here
Add distclean target (does not work fully yet, needs to be made recursive)
Corrected distclean target for Linux systems. Removes cmake cruft for in-source builds.
Make clean before distclean
Update #includes to be relative (we should not assume fastlib/ is always in the include path, this keeps it simple).
Make #includes relative to fastlib
Move CMake utility files to root directory of build (cmake should be run from there).
One more #include relativity fix
Revamp cmake:
Revamp cmake structure again. Builds all targets each into their own directory as well as linking into libfastlib.a, making building it all as well as working on individual components simpler. CMakeLists.txt files also commented and clarified to be less confusing.
Oops, misspelling. Dangerous because it would compile fine but would not link fx into libfastlib.a.
Do not make intermediate libraries; just collect filenames of files to be compiled into libfastlib.a.
Don't build intermediate libraries, compile everything into libmlpack.a
Update include directories
Move header files to correct directory in build (include/mlpack/)
Install header files correctly into include/fastlib and include/mlpack.
Set svn:ignore to 'build' in root dir
Copy over contrib directory so that I can start adapting build.py to cmake
Require 2.8
What? Somehow missed copying over emst in MLPACK. Commented out cmake MLPACK program install guidelines, they need to be redone.
Add emst to cmake build.
Remove some unneeded comments. Test for doxygen-update on churchlady
Include thor in build (it was not there) and move mmanager over, to be tackled later.
cmake build information for thor
end(), not last(), and fix some fx syntax which has changed
Huh?
Fix differences in function signatures (.cc implementations were using const char *)
Set up cmake infrastructure for contrib, and by default compile those which already compile without me having to fight with it too much
Oops, still have to set up physpack with cmake (should be very simple)
Set up cmake for physpack (do not build by default)
Make sure executables are installed correctly (may still need polishing)
Apply same change from branch to trunk ("Huh?")
Huge merge of fastlib-cmake into trunk, done all wrong (svn merge failed... surprise?). All the CMakeLists.txt files have been copied over and all of the other relevant CMake files too. I've done my best to keep it as simple as possible but unfortunately that was not entirely feasible here.
Revert 'src' to 'fastlib' so I don't break everything fl-build does.
Fix nnsvm so it builds correctly (fx_ calls were out of date) and add to CMake build
Add mmapmm to fastlib build. A few code changes were necessary stemming from some earlier base/basic_types.h changes.
Move code that finds trilinos out from sparse CMakeLists
Add kernel_pca (which required sparse) to default build, modify a few things (ticket #13 is related) so it compiles fine
Need to figure out why those two lines have been causing issues
Don't use local trilinos headers, use system ones (it's CMake's job to figure out where these are)
mmapmm support by default in fastlib means a lot of these methods now compile right
Incorrect #include line, should use relative paths for fastlib stuff
#22: replace lots of preprocessor macros with what they actually are where possible.
Missed these macros
Allow selection of SCALE_MASSIVE, SCALE_LARGE, or SCALE_NORMAL in CMake configuration (default to SCALE_NORMAL if not otherwise specified, and check to make sure multiple options are not selected)
Use boost::serialization and boost::program_options and link against both (to be integrated into trunk)
uint -> unsigned int (same thing but 'uint' does not exist on all platforms apparently)
Do not build mlpack_contrib or any of its pieces by default
posix_fadvise is not defined on all systems
Create fastlib-armadillo branch, where we will attempt to try to replace GenMatrix with armadillo's implementation.
Fix for #26; forgot the type specifier after LI (since the LI macro now requires a type after it, so it works for all types)
Fix #27: incorrect use of LI macro (same as #26 but this fixes it in the fastlib-cmake branch)
Fix syntactical errors in CMake files
Allow TextFile to return its own filename
Add compatibility layer to convert between Matrix and arma::mat (this is NOT fast! but it's only here for compatibility)
Add header inclusion guards (how did I forget these?), clean up formatting of base.h
Separate dataset classes into separate files, and then adapt them to use arma::mat internally (as well as on their external interfaces). Update CMake to include our new files in compilation.
Use arma_compat layer to allow Thor to interface with changed Dataset API
Update all MLPACK methods to use arma_compat layer so that they can use the new Dataset interface. Eventually all this arma_compat stuff should be removed, but for now it is fine.
Add useful compat function which emulates Matrix::MakeColumnVector() functionality (albeit slowly)
Ensure each built library links against BLAS (#28). Apparently this was fine on Linux systems but failed on Macs; hopefully this will solve the issue.
Don't use deprecated values.h; prefer limits.h and float.h instead.
Rewrite tree to use armadillo.
Update mlpack methods for tree API changes
Split up bound classes into separate files for each class, and then separate files for interface and implementation.
Stop using GenVector in data (quick and simple replacement)
Add GenVector to arma::vec compatibility functions to arma_compat::
Change TAU to a preprocessor constant to fix odd linker error on Mac (or at least attempt to)
Change name of variable so -D TRILINOS_LIB_DIR=... can be used
Rewrite LMetric<> to not use GenVector by default, then modify a couple other files so that all works.
Fix calls to LMetric<>::Distance() to use arma::vec with arma_compat layer
Rewrite DHrectBound to use arma::vec internally and in its interfaces. The kdtree methods needed some modification and one needed to be moved into an implementation file (since it was not templated).
Modify thor methods to work with change of DHrectBound
Modify MLPACK methods to work with DHrectBound API change
Update TKdTree methods to use armadillo vector and matrix instead of GenVector and GenMatrix. I also removed unnecessary uses of ArrayList, replacing with arma::vec where possible.
Fix calls to TKdTree assembly methods; replace ArrayLists with arma::vec for what are essentially fixed-size arrays (ArrayLists were unnecessary for the application)
I'm pretty sure the user is aware of what they typed. Don't echo it when they type --help.
Unfortunately, CMake won't work at all if it's being told to configure directories that no longer exist, so I commented out the directories removed in r5575 so it won't freak out anymore.
Link against mlpack and Trilinos
When a user enters no parameters or -h, fake it so FX thinks the user is asking for help.
Did not mean to commit this minor change; it turned out to be unnecessary
Make parameter description give --submod/param instead of --param to eliminate confusion
Modify fx output format a little bit so it's a bit easier to understand. Code is ugly but it works... I can't wait to rip this entire system out and replace it with something sensible
More accurate documentation that meshes better with help screens
Oops, fix -h and -help
Update documentation so that it actually works, and make sure we tell the user that they can actually give a dataset as a parameter
Add cheap utility CSV saving method for allnn
Is this a joke? I mean, seriously! allnn ships with no actual way to save the data that it's calculated; I've rewritten so that it might actually be useful to someone, ever
Set required parameters and defaults for non-required parameters
Properly document allkfn, which was not done at all. Maybe now, people can use it!
Properly document the allknn method.
Update some mistypings in allkfn documentation
Document emst; remove non-working --use-thor parameter. Names of some parameters changed for consistency across all MLPACK methods.
Add documentation on file formats for HMM utilities
Rename HMM executables to things that will not potentially conflict with other utilities on a user's system
Document hmm_train executable entirely, and change some outputs from printf to fastlib standards where necessary
Looks like my brain tripped on terminology
Change some parameter names to indicate where model files are required
Document the hmm_generate executable
Documented hmm_loglik utility thoroughly
Remove usage() declaration
Documented hmm_viterbi utility
Update documentation partially; it was noticed that this does not work successfully. I put in some debug information
Update CMakeLists to properly install fastlib and mlpack.
A readme to get installed to /usr/share/doc
Install README_MLPACK is /usr/share/doc
Tag fastlib-0.4 release.
Add GPLv2 as license and copy doc/README_MLPACK to README
Finish transition of tree to arma::vec and related classes, and remove some methods that were commented out and unnecessary
Remove last references to Vector class
Correctly initialize DatasetFeature members during Init(); it should be noted that the features_ vector does not clear() itself upon calls to Init*() methods, but this will be irrelevant when we ditch the Init() style of methods and use constructors.
Ugly hack to get around failure of math::MakeIdentityPermutation() -- should be using fixed-size arrays there (todo).
Preprocessor macros are bad when they make programs perform in ways users don't expect.
Add new parameter to tokenizeString that will save the last token if a stop character is encountered. Make it look a little nicer with a few comments and a using directive. Also, fix the last condition (should be || not &&) to capture the last token if necessary.
Initialize int correctly in SkipSpace_().
Fix ReadMatrix() (it was trying to write to places that don't exist). I think the implementation in fastlib-armadillo is less bizarre and will end up being used here (arma::vec lends itself better to this task than std::vector). Need to merge those branches...
Rewrite the ReadMatrix() code to be almost identical to that found in fastlib-armadillo. Should have merged them earlier...
Merge fastlib-armadillo/fastlib/base into fastlib-stl/fastlib/base
Merge branches/fastlib-armadillo/fastlib/file into fastlib-stl/fastlib/file
Merge fastlib-armadillo/fastlib/data with fastlib-stl/fastlib/data. Runtime dataset_test fails, but it compiles ok.
Fix bugs introduced into DatasetInfo of my own doing.
Merge fastlib-armadillo/fastlib/optimization into fastlib-stl/fastlib/optimization
Merge fastlib-armadillo/fastlib/thor into fastlib-stl/fastlib/thor
const char * --> std::string
More std::string usage
Failed merge not noticed until template function instantiation...
Merge fastlib-armadillo/fastlib/tree with fastlib-stl/fastlib/tree. This should
Merge all??n methods from fastlib-armadillo/mlpack into fastlib-stl branch
Fix allkfn so allkfn_test compiles (however, it throws an error)
Merge last bits of fastlib-armadillo/mlpack into fastlib-stl/mlpack
Merge fastlib-armadillo/contrib into fastlib-stl
Merge CMake files from fastlib-armadillo into fastlib-stl
Merge changes to CMakeLists.txt from fastlib-armadillo branch to fastlib-stl
Remove fastlib-armadillo branch; it has been successfully merged into the
How did this happen? Oops...
Fix bug introduced a while ago; when quicksorting to build the tree, we have to keep our local matrix up to date (the temporary matrix we passed is modified)
Remove ridiculous copypasta from AllNN::Init() and AllNN::InitNaive() (it could
Compile with debugging information by default (so that DEBUG_ASSERT_MSG and similar macros will still work, as they are DEBUG_ONLY).
Oops, we need to tell the compiler to set the DEBUG macro flag.
Custom DistanceSqEuclidean() function for arma::vec objects.
Remove last instances of Matrix and Vector from allnn.
Changes in contrib/ affected and broke kde/, so don't bother with that for now
Function specialization is no longer necessary
Remove last references and uses of Matrix from AllNN class.
Remove Matrix, Vector, and ArrayList classes from allknn. Compiles, but test does not pass.
Add debug option to stl branch
Turns out this is a better way to define the DEBUG flag (and by better I mean... it works)
Propagate change from trunk CMakeLists.txt to branch... properly use DEBUG definition when told to
THIS IS YOUR BRAIN ON DRUGS
We require different modifiable input matrices as input to AllkNN for now. That will have to be changed. (tree generation modifies the matrix)
Fix allkfn to not use Matrix or Vector anywhere. This one was very easy because it's so similar to allknn. Could it be... time for refactoring into a sensible hierarchy to maximize code reuse and minimize the codebase? Well... not yet...
Fix main executable to stop using Matrix or Vector or ArrayList entirely.
Build union_find_test target
Remove Vector and Matrix and ArrayList uses from emst method. There is no test for emst, so that will have to be done.
Convert linalg__private::Center() to armadillo. Created unit test file, because damn, these things get complex and I want to know that they're working right.
No. We will not be outputting BLACK text. No.
Rewrite WhitenUsingEig(). Fix simple (yet fatal) bug in Center(). Test case for WhitenUsingEig() also added, but perhaps at some point should be made more thorough.
Extend functionality of Armadillo; cov() operates like Octave, but what we want is
Rewrite FastICA Orthogonalize() method and write a test for it.
FastICA now compiles, but I'm sure it doesn't work, and it hasn't been tested. The vast majority of methods from lin_alg.h have been pruned as they are no longer necessary.
Find and set up Opt++. I don't like that I did this but I had to.
Add CMake script to find Opt++.
Make optimization work. The test doesn't, but it compiles and runs otherwise (test appears to be severely out of date).
Fix MVU/MFNU so that it works.
Allow compilation of mvu
Significantly improve (by a factor of 1.5 or more) DistanceSqEuclidean function.
Speed improvements for MinDistanceSq().
Improve speed of AllkNN methods by using new armadillo mat::unsafe_col() method (returns an arma::vec alias which uses shared memory from the matrix).
Apply use of unsafe_col() to allnn and allkfn for speed improvements.
Include arma_extend files in build and then install them to the include/ directory.
Revert math::Pow functions in case old code still uses them. They can be removed later on.
Do not make test in default build (it fails).
Fix syntax errors introduced in lbfgs methods in r6232 and r6233.
Apply changes from r5648 to fastlib-stl branch (allow selection of number of independent components).
Remove some amount of debugging output. Fix DeflationLogCoshUpdate_() (was missing a "- n" term) so that FastICA now performs nearly identically to the trunk implementation.
Fix "translation" errors in DeflationGaussUpdate_() and fix spelling in comment.
First pass at version requirements for Armadillo. One thing left to do; when looking at version.hpp (not arma_version.hpp) the syntax is different, so I need to rewrite the regular expressions.
Update regexes to correctly parse version information for older versions of Armadillo.
Set up optimization CMake configuration correctly
Use source root directory as include directory instead of ${CMAKE_BINARY_DIR}/include. With the latter, the compilation will look inside of the built include files. Therefore, if a user makes a change to an included file, it isn't reflected in the build. This change fixes that.
Replicate r6607 in trunk; prevent odd compilation situations where modified included files aren't actually updated.
arma::Mat<eT>::unsafe_col() was introduced in Armadillo 0.9.90 (require that). Only problem is, that hasn't yet been packaged by the Ubuntu maintainers.
Refactor AllNN into header and source file since it's not a templated class (that may change). Copy the main executable over from trunk, where I modified it more heavily, then transition to armadillo components.
Fix bug in TextLineReader::ReadLine_().
Add an overload of data::Save() that was necessary for trunk allnn.
Fix two bugs -- the first is a forgotten reference specifier. The second fix ensures the same tree is not built twice (if you pass the same matrix for queries and references); additionally it prevents the same point from being reported as its own nearest neighbor.
Rewrite bits of HMM so that they compile. This is not tested at all (and not expected to work right), but the changes made here mainly serve to make the buildserver happy with this branch.
And I was so close to getting it all right!
Test checkin from ryan to see if anonymous checkins are really allowed now
Formatting pickiness changes from gcolon7's r6924
Test checkin
Update series_expansion methods to use armadillo and std:: components.
Update promixity_project code (which some MLPACK methods have a dependency on) to use armadillo and std:: components
Update naive_kde to use armadillo and std:: components
Change KDE utility classes to use armadillo and std:: components
Update all dualtree KDE methods to use armadillo and std:: components (not tested -- only compiled).
Convert FFTKde methods to armadillo and std:: components (not tested)
Convert FGT-KDE methods to armadillo and std:: components (not tested)
Check in converted dualtree KDE method file that I missed (not tested)
Convert original IFGT methods to armadillo and std:: components (not tested)
Last of KDE methods converted to std:: and armadillo components (not tested)
Some fixes that I missed in series_expansion (now KDE should compile fine, but again is untested)
This file isn't actually even used. Remove it.
Update NNSVM methods to use std:: and armadillo components (not tested, but it compiles)
Change fourier_expansion to std:: and armadillo components (not tested, but it compiles)
Disable compilation of methods that require sparse because sparse support is essentially nonexistent.
Don't crash out when mlpack_contrib.a does not exist
Ack, I forgot that I had added this line
Remove Init() functions for AllNN. Everything is now part of the constructor, and initialization lists are used.
Oops, I broke the build again. The constructor changes have to be propagated to
Remove deprecated constructors from AllNN.
Remove ComputeNaive() and put that functionality into ComputeNeighbors(). Since
Remove unused function; I forgot I had left this here.
Did I really forget to delete these declarations too? Apparently today is not
Move into mlpack::allknn namespace; and separate implementation from declaration
Update mvu code. At this point it does not work but it does compile.
Unbreak everything: update references to AllkNN: AllkNN -> mlpack::allknn::AllkNN
Refactor AllkNN API; move Init() functions into constructors; update tests to
Update KDE to use newer AllkNN constructors.
Update CMakeLists for L-BFGS optimization method.
Remove old build.py files. As per #14.
Revert accidentally committed debug output changes.
Remove the fl-build tool (#14). Did I break your build by doing this? See
Replicate r7054 in fastlib-stl branch: remove build.py files (#14).
Replicate r7056 in fastlib-stl branch: remove fl-build and fl-build-all (#14).
Remove FORTRAN from CMake configuration. Turns out we don't actually need it, and I never thought to check until now.
Remove FORTRAN from CMake dependencies. (see r7124)
Don't modify CXXFLAGS at a lower level (this was causing MLPACK to compile
Fix incorrect usages of std::pow introduced in r6231. I can't believe how long
Add mode option and display number of pruned nodes.
Don't include Makefile in the repository, it is a build artifact
Don't include Makefile in the repository, it is a build artifact
io_test does not exist in the repository yet; commented out for now. Also fixed
Do not attempt to continue if the dataset did not load properly (#32).
Comment out function that was defined twice.
Link against armadillo too.
Remove FORTRAN from CMake dependencies. (see r7124)
Refactor AllkNN entirely.
Better implementation of MinDistanceSq(DHrectBound& other).
Oh dear God, I've forgotten a space!
Code formatting fixes, mainly.
Refactor allkfn.h into allkfn.h and allkfn.cc. Then, remove Init() and
Move AllkFN into mlpack::allkfn:: namespace. I find mlpack::allkfn:: very
Add additional pruning; not necessary but I think it gets us a speed boost (I
Don't use std::vector<std::pair<double, index_t> > to store lists of furthest
Boost exceptions are not actually being used and this header file does not exist
Remove Nick's implementation of an augmented Lagrangian which uses L-BFGS, which
Copy Dongryel's implementation of L-BFGS.
Update CMake configuration.
Comment out pagarwal directory until CMake configuration is added inside of it
Do not use local include
Adapt L-BFGS method. Wrote test function (RosenbrockFunction) and will adapt
Don't compile optpp directory (it does not work).
Add WoodFunction and GeneralizedRosenbrockFunction (adapted Dongryel's
Adapt L-BFGS implementation to optimize matrices instead of just vectors (this
Implement r7435 changes into this implementation of L-BFGS. Also, for
Fix errors: missed conversion of arma::vec to arma::mat in a couple of places.
Add a test function with a matrix to optimize (to make sure that L-BFGS is
Remove L_BFGS::Init() and use the constructor instead (in accordance with MLPACK
Do not provide a GetDimension() function; the user should get that from .n_cols
Don't build LARS by default
Don't build contrib stuff as it has not yet been converted to Armadillo and stl.
Make all error/warning/info prefixes 5 characters wide (NOTIFY -> INFO). That
Add augmented Lagrangian method. No tests or implementation yet.
Fix formatting error.
Fix several errors inside of AugLagrangian.
Add test function and test for AugLagrangian. Compiles, but does not yet work.
Update CMakeLists for new AugLagrangian test.
Fix Lagrangian calculations (I had a sign wrong) and terminate when little
Make AugLagrangianTestFunction work, and also create new test function (which
Reduce gradient norm check value, and add some useful output (as comments).
Be more stringent with Armadillo version checking; fix regex for checking if parsing was correct.
I like it when my code compiles
Return a bool instead of an int (this is C++, not C, so we have this nice type).
Remove stringification from macros (users should pass in strings in quotes
Transition to IO in a more complete manner.
Comment out IO parameters for now. We'll come back to this later.
Document PARAM() macro and add PARAM_*_REQ() macros. Documentation should be
Make relevant parameters required.
Well of course, I forgot to check something in and I broke the build...
Make iostream-based output system. I still have a concern, though, which is
Don't add std::endl at the end of output (this doesn't work right). We can
Remove Print*() functions from io.h and change internal IO calls to now use the
Adapt to new IO output API.
No using directive in header files, this makes angry worlds happen.
Grammar Nazi strikes again
Remove extra unnecessary newlines, even though this class will be going away
Don't show missing required option warnings before giving help, and make those
Missed all this stuff and broke the build. Adapt output to the new IO API.
Compile with optimization when not in debug mode, and prune arbitrarily long
Don't overwrite CFLAGS and CXXFLAGS.
Add contrib directory and the code I have used to learn a metric for AllkNN; I will be submitting the results to MLSP 2011.
Turn sparse off by default (because it doesn't work). Require optimizers for
Revert r7929, which I think was an accident.
Commit the change that I think r7929 was supposed to be: fix compatibility with
Update distance learning code; more documentation on parameters and use FDSA for gradient estimate. I could probably use to clean it up a little more but I'll postpone that until after the paper deadline...
Add support for 64-bit types (u64, s64) to our little Armadillo extension
Add arma_extend.h to fastlib.h so that a user does not have to try to include it
It's not used, it's bulky, useless, and bloatful. DELETE
Their eyes were bright and optimistic as they implemented a complex parallelized
We don't need a ComplexVector class; we can use Armadillo just fine for that.
Don't include the file we deleted...
Don't include a file we deleted...
#17: remove horrifying object traversal library.
#17: Remove object traversal madness from base FASTLIB classes where necessary.
#17: Remove object traversal madness from MLPACK methods.
#17: Remove object traversal madness from something on contrib/ which something
Clean up includes for NBC
Remove last references to object traversal.
Remove ccmem.h and ccmem.cc. No more mem::. Glory ensues.
Remove RangeSet, DenseIntMap, and fast allocation routines. They were not used
Nothing in par/ is used anymore (with THOR gone). Remove it.
Update header files for removal of par/.
I don't know why this test was never included. Anyways, it works fine.
Minor useless change to see if Doxygen is being regenerated on commits.
Another useless checkin for testing Doxygen regeneration.
Update includes, do not use fastlib_int.h.
Don't use fastlib_int.h.
Remove fastlib_int.h.
Remove deprecated.h (hey, it's all deprecated, right?) and an unused macro or
Always make sure you are properly fed when you code. Otherwise, you risk
Half-solution for when __COUNTER__ does not exist.
Fix a minor spelling issue and add a comment noting why we don't have to worry
Fix warnings about non-virtual destructors (which didn't actually make a
Make FATAL output stream actually cause the program to die. Update test to
Oops, this isn't included by default.
Half-revert r8133 to use __USE_ISOC99; update CMakeLists.txt to issue -std=c99
Use IO output instead of NOTIFY and related macros.
Allow PARAM macros to accept default values.
Set up CMake to use Boost.Test
Change allknn_test to use Boost unit test framework. It works.
Revert changes by nkauffman3 to unbreak build
Testing class no longer exists, and fix some formatting issues
Although the C++ reference site gives all these functions as taking a reference,
Add operator<< support for armadillo objects when using IO output components.
Rewrite armadillo output functions just a little more to correctly utilize the
Sanity check on input parameters.
Rewrite help output formatting for IO. We needed a helper function to hyphenate
Fix odd formatting issues in io.h
Add PROGRAM_INFO() macro (and related support, including ProgramDoc class) to
Derpy derpy derp derp hurrrr
Change BOOL to FLAG. Clean up output a little bit more -- sort the types of
Change BOOL to FLAG
Update from BOOL to FLAG and remove default parameter.
Remove default parameter for flags (it is always false).
Allow newline characters in hyphenatable strings.
Update program documentation.
Convert L-BFGS optimizer to use IO-style output. Also change test to use
Update AugLagrangian to use IO-style output and use Boost.Test framework.
Add IODeleter class to ensure that the singleton actually gets destroyed someday
Remove Printing classes because they are no longer necessary (see changes in
Fix includes for PrefixedOutStream and NullOutStream.
Fix more includes for IO; remove some unnecessary includes from io.cc (since
Reintroduce needed TYPENAME() macro.
Update AllkFN test to use Boost Unit Testing Framework. Also switch to IO
Write exhaustive check which provides a lot more coverage of the functionality
Make same optimization change for single mode optimization -- don't use
Comment recursion a little better; fix bug for corner case where the number of
I sat down to make a SetParam() method until I stupidly realized that GetValue()
Uncommit another repository from within this repository
Undo r8255 since the changes to IO-style output were already done for these two
Unmerge svn repo-in-repo, 2nd time.
Entirely refactor AllkNN into templated NeighborSearch class. This allows
Add core/kernels directory to start work on #78. Only one kernel for now
Don't compile mvu; it is not necessary for now (but it is under development and
Update instantiations of AllkNN to reflect constructor changes.
AllkFN has not been transitioned to NeighborSearch yet.
Oops, I made an unstable test (fixed).
Remove allkfn because it is now a part of the neighbor_search class.
Expand NearestNeighborSort SortPolicy class so that the NeighborSearch class is
Transition AllkFN to NeighborSearch, adding FurthestNeighborSort policy class so
Convenience typedefs for AllkFN and AllkNN.
Update CMake configuration to remove allknn, allkfn, and allnn, using now
AllNN is no longer necessary; it is simply AllkNN with k = 1.
Clean up code, adding some comments, and make names of variables truly agnostic
Add exhaustive test for AllkFN. A lot of code duplication...
Add tests for sort policy.
Glaring typo fixed
Move LMetric class to kernels to replace L2SquaredMetric with something more
Add test for kernels and remove L2SquaredMetric
Update tree code to use LMetric which is now in mlpack/core/kernels/.
Change from L2SquaredMetric to SquaredEuclideanDistance.
Update from old LMetric class to new one in mlpack/core/kernels/.
Add MahalanobisDistance kernel and corresponding tests to make sure it works. I
MinHeap? More like MinDELETED BECAUSE NOBODY CARES
What is this crap and why is it here? This is not the place for it...
Undo r8363...
Use explicit floats for older versions of Boost UTF
Fix error which only appeared on gcc < 4.3; the __COUNTER__ macro is not
Explicitly specify floating-point numbers for BOOST_REQUIRE_CLOSE().
Move parameter options around so conflicts don't occur when using gcc < 4.3
Aha! Found it. This fixes the segfault.
Add PARAM_DOUBLE macro just in case someone wants it over PARAM_FLOAT. Really,
Don't include FX in weird contrib file which is included in MLPACK
IO test should not display output because this breaks the build server...
Update test, which was incorrectly written to test Center() on matrices which
I would like ten million output for debugging the build server please
Revert r8434 because it introduced a bunch of errors and now I can't use IO the
Revert r8434
Fix assignment of delta_f in CalculateDF_(); it was using w_square_sum_, which
I am unsure about the validity of my changes, but fix small differences in the
Add new methods/ directory, where we will move all the MLPACK methods to
No more notification for debug builds using this mechanism.
Have IO output information if the program was compiled with debugging symbols
Add a few introductory tests for SoftmaxErrorFunction.
Make debug output only show if IO was used to parse the command line; this way,
Fix a few warnings I caused, and remove some unnecessary warning output (it
Remove some IO warnings that aren't actually dangerous and fix some build
Add tests for the evaluation of the objective and gradient of already optimal datasets.
Add test for the NCA algorithm. Needs hand-calculation of optimal output
Remove these files because they are not part of the L-BFGS optimizer. We may
Transition the L-BFGS optimizer to use IO parameters. Now for things that use
Fix error in L-BFGS test. [] only takes one argument and will ignore the
Clarify documentation slightly for the L-BFGS module.
Uh, I mean, don't break everything forever. How did I forget that...?
Fix some grammar and spelling, make documentation wrap correctly for modules,
We can't know the final optimal matrix because it is not necessarily unique, but
Warnings all the time for all build types
Fix unused variable warning
Symlinks? Really?
Remove disk_allnn. It was never used, it will never be used, and it can be done
This simply isn't used anymore.
Actually revert Noah's changes to ridge regression.
Actuall revert Noah's changes to Kernel PCA.
Actually revert Noah's changes to Infomax ICA tests.
Actually actually revert Noah's changes. I blame exhaustion.
Write the NCA softmax error function in a more computationally friendly way.
Do not use these small CSV files; hardcode the values into the test program.
Fix compiler warnings by converting from fprintf()-based file I/O to
Fix #91: newer versions of Armadillo require a different style of magic to
Output doubles too
Retool IO a little bit to allow the output of timers. This involved modifying
Oh no. We cannot forget this space. It is very important. Otherwise, the user
Give convenient divisions of timers so users don't have to do the division
Don't use NOTIFY. Wow, that is a horribly written test, by the way.
Don't use VERBOSE_MSG.
Let's try not leaking memory everywhere.
No more VERBOSE_MSG or VERBOSE_GOT_HERE or VERBOSE_WHATEVER. Transition to
Remove NOTIFY_STAR, NOTIFY, VERBOSE_GOT_HERE, and VERBOSE_MSG.
Don't use NONFATAL or FATAL.
Remove some odd code...
Stop using NONFATAL and FATAL.
Don't include base/test.h.
Don't include base/test.h. And remove base/test.h.
Remove uses of DEBUG_WARN and DEBUG_ERROR macros.
Specify mlpack namespace
Only try to add new things to the hierarchy if they are timers. This helps the
Sometimes splitpos gets higher than the length of the string, and we don't want
Add a little bit of documentation.
Limit to 10k iterations as opposed to 10M for the test.
Force lambda to be updated immediately at the end of the first L-BFGS
The code is incapable of running the first test, so comment it out entirely.
Don't use external files for the test. And clean up some odd formatting...
Copy ARFF files to correct place for Naive Bayes tests.
Implement Lovasz-Theta SDP, but it does not work and pass the test yet.
Debugging output, probably temporary.
Return true when the gradient norm is too small, because in that case the
Use Mat_meat.hpp, which has not changed over Armadillo versions, but arma_ostream_proto.hpp has changed names.
Update the Lovasz-theta SDP constraint conditions, which in Burer's formulations
Remove unnecessary debugging output.
Put a few things into the correct namespace, and split definition and
Update trees because they are now in the mlpack::tree:: namespace.
Split kdtree.h implementations out to kdtree_impl.h and put it all in
Use typename instead of class
Start refactoring BinarySpaceTree. First stop: constructors.
Rewrite to stop using MakeKdTreeMidpoint() and start using constructors of the
arma::linspace() fails with one dimension for earlier Armadillo versions. So...
Optimization: don't set the bounds of the splitting function just does that
Change ordering of initialization lists, and initialize left and right members.
Missed one constructor.
Add a lot of comments. And delete unnecessary code in SelectMatrixPartition(),
Avoid vector copies. They are bad.
Remove unused methods.
Add profile option
Add this test case for Bill to try out. We needed to make count_ public
Add the cosine distance. It is not very extensible at the moment but I think
Actually, we implemented the cosine similarity. If we want it to be the cosine
Remove cross-validation mode from SVM.
Remove cross-validation code. Solves #86.
Revert count_ to being private and update test.
Due to the way constructors work in C++, it is not possible for this check to
Refactor QueryStat to not use Init(). And remove an ugly space...
Remove kdtree.h and other files. All functionality is in spacetree.h now.
Remove tree/kdtree.h from includes.
If we choose to implement a Kalman filter later, we will do it from scratch.
Neither of these things is useful to us.
QuicSVD goes away. Who the hell knows if it ever even worked?
Put EMST into mlpack::emst namespace. Use LMetric instead of la:: distance
Remove KDE. If we reimplement it we will restart from Dongryeol's version.
This tool is stupid. Bye!
This doesn't depend on QuicSVD. The documentation for the program is full of
Stop using la:: and arma_compat.
Stop using la:: and arma_compat. No comment on utterly bizarre function which
Stop using arma_compat and la::.
Stop using la:: and arma_compat.
Convert from GenVector and GenMatrix to arma::vec and arma::mat, respectively.
Stop using arma_compat.
arma_compat is no longer needed because it is no longer used.
Stop using la/ and stop using arma_compat.
Remove GenMatrix and GenVector. I have waited so long for this day, and it came
Don't use newer call to inv().
Remove sparse matrix support. It is not used.
Stop allowing SPARSE option and do not look for Trilinos anymore.
Reshape to one column, not one row. This fixes a runtime error.
Comment out n_point directory until CMakeLists.txt is added
Remove two unused methods.
Change some documentation to be more clear.
We force TDataset to be arma::mat always, so remove it as a template parameter.
Adapt tree usage to not require parameter for TDataset.
Add destructor to clean up memory... why didn't this exist before?
Agh space
This example is horribly out of date and we would be better off rewriting from
The little utilities contained herein are no longer deemed useful. We can
Nothing in these directories... they do not need to exist.
Missed this directory which does not need to exist.
Remove all of the script files. We will need to write a new tool to make
Don't take leaf_size_ as a parameter but instead abstract it out to IO.
Remove leaf_size_ parameter so that we can use the tree's one instead.
Document the "tree" module.
Solve #103 and add a test to verify. Maybe it would be nice if the Armadillo
Removed the special Armadillo PrefixedOutStream operators since it is not needed
Armadillo versions newer than 1.2.0 don't need u64 typedef'ed.
The name of the 'promote_type' structure changed to 'is_promotable' in Armadillo
Well, there's your problem.
I must be missing something, it seems like u64 is not actually defined on older
Actually, the issue is that the header file exists but Armadillo does not
My comparisons were wrong. Also, no need to put u64 in the arma namespace; it
Remove last unlikely
Force BOOST_REQUIRE_*() arguments to be doubles for older versions of Boost.
More meaningful and complete tests for PrefixedOutStream.
Clean up and refactor the PrefixedOutStream class, and fix a few bugs Pari
Make sure the Armadillo header is included correctly.
Move inline function into implementation
Remove basic_types.h since nothing in it is used anymore.
Oops, not supposed to comment out everyone else's directories.
Spaces after if statements
Parameter names changed; update for that.
Set a default value for boolean options (false).
By default, verbosity is off, and is only set on if we parse --verbose (the
Also test Boolean options.
Make --help a flag, and initialize tmp correctly to clean up a warning.
Oops, forgot to add that third parameter.
Add Armadillo output support to NullOutStream, and format the file a little more
Remove some unused options, and add some code which could do PGO if we were
Remove several files in base/ because they are not necessary any longer.
Remove common.h (which had nothing useful in it) and put that in fastlib.h.
Remove Opt++ support as it was not being used.
Remove contrib/ as it was not being used. The items within will be
Remove some cruft
Remove some space (I am doing some testing of svn hooks, so don't mind the
Update lin_alg_test for #85.
Clean up NBC test
Move to more simply named 'nbc_test.cc'.
Remove unused test_infomax_ica.h, and move test_main.cc to infomax_ica_test.cc.
Convert series_expansion_test to Boost UTF, and fix a bug which caused a
Fix some formatting, give the test a better name, and strip trailing whitespace.
Deletin' the whitespace for future generations. And, fix a bug I managed to
Comment out unused variable.
Use GetParam<> for bools, not HasParam().
Make sure we terminate when our stream is fatal.
There was a case where we did not start the program timer.
physpack/ was not used and we will not be maintaining it. It may be
Remove stray spaces
This file is not used and not necessary...
DefaultMessages() was commented out for some reason, leaving --help
Reformat offensive code. Delete some unused code. This code needs help...
Split definition and implementation into separate files.
Place SVM components inside mlpack::svm namespace.
Use IO output and remove mlpack:: where it is not needed. A few more code
Remove series_expansion to clean up some stuff in math/. If we reimplement it
Require libxml2-dev for Neil's future work in saving SVM models.
Don't count on a using directive from somewhere else. Use arma::vec.
Refactor the interface for DHrectBound; change to HRectBound, and simplify a few
Update DHrectBound to HRectBound.
Change a few things about how Doxygen works.
Reverse-merge new tree test which did not account for change in DHrectBound
Refactor DRange out of math_lib.h and then rename it just Range.
Implications of DRange -> Range name change.
Clean out a lot of Range code, making the class far simpler. I don't think I'm
Prune more unused functions of Range. Don't use Init-style functions anymore;
Update tree test to not use Init, and use the default constructor in the bounds
Add a test for the Range class. It is a proper unit test and tests every
Clean up kd_tree_test.
Move dhrectbound.h -> hrectbound.h to reflect the class name change. Also clean
This MVU implementation still has some bugs but before I move everything around
Update to use IO instead of fx.
Start writing actual unit tests for HRectBound.
Make the new /mlpack directory. The future: it is here.
This checkin will make coffeetalk-1 happy and heat up the frigid CoC server
Make repository structure standard svn-style.
Move configuration for fastlib to mlpack. This is for Jenkins and the packaging
Restructure MLPACK directories to the format suggested in #2.
Move some things out of fastlib/ and put them in src/core. I will destroy the
Finish moving out the last of the fastlib/ directories.
I have waited so long to do this. I really have, I mean it.
I have waited so long to do this. I really have, I mean it.
Clean up root CMakeLists configuration a little bit, and remove FASTLIB.
Move all the MLPACK methods into src/methods.
Clear up CMake configuration.
sparse_censorship was removed so we should take it out of the CMake
Update all CMakeLists.txt files to reflect new directory structure. Remove any
Move everything to src/mlpack and src/contrib. This makes the setup a little
Update all includes so that things work and compile again. A couple MLPACK
Add that core.h file which we were using in place of fastlib/fastlib.h.
Directory structure changed so we need to copy tests from somewhere else now.
Move header files properly to <builddir>/include/mlpack/ and then install them
Remove PI; it is included in math.h, although with less precision.
range.h and kernel.h are no longer included in math_lib.h.
Stop using math::PI; use PI contained in <math.h> instead.
Stop using math::PI
Stop using Sqr(); use pow(x, 2) -- it is faster.
Don't use Sqr(); use pow(x, 2) -- it is faster.
So it's actually M_PI not PI. What am I smoking today?
It's actually M_PI not PI.
Include the correct files since math_lib.h no longer does that.
Make sure we include M_PI, and if the system does not define it for us, we'll
Be a bit smarter about what we glob. We don't want .h.swp and we don't want
Make MOG compile. I am certain it doesn't work because I know I broke it in a
Orthogonal range search will be too difficult to preserve and we should start
Finish the unit test for HRectBound, completely. Took a couple of methods out
Make sure all of the arff files get into place.
Rename DHrectPeriodicBound to PeriodicHRectBound. Remove the test for now.
Change the name of a few methods in PeriodicHRectBound to match. Implement
Fix two warnings relating to unsigned/signed comparisons.
Don't compile the main executable and test executable into the library itself.
Update CMake configuration to not comment out everyone's code (only most of it).
Oops, we wanted the name of the file, not the vector.
Idiot Ryan is idiot idiot idiot idiot
Resolve #142 by removing the problem entirely.
Clean up code; make helper functions more generalized; grammar Nazi. Use L2
Clean up the code. I think we can make it a little faster by how we do the
Simple Doxyfile changes. Let's see if we generate the right API.
Update Doxygen configuration.
Shooping the whoop on our Doxygen configuration.
Write the main page of Doxygen documentation.
Doxygenate? Doxygenize? Doxitize? Doxify? Doxenation? DOXY NATION!
Clean up some more Doxygen.
Make a custom stylesheet for our Doxygen output so it matches Trac.
Some changes so it works with Trac. I'm sure I didn't get it all right.
A couple changes to make it work right with Trac.
Just a couple CSS changes.
A few more changes because monospace fonts are not being used in the right
Oops, I broke the local documentation style. This should fix it.
Add an example kernel for documentation purposes.
Document GaussianRBFKernel just a little bit better and clean up the code.
Apparent inability to perform simple math
Check .hpp and .cpp files for documentation also.
Refactor and comment GaussianRBFKernel. Rename it GaussianKernel.
Comment CosineDistance. Fix a problem I introduced in GaussianKernel. Rename a
Document the linear kernel. Rename some files.
Add a few contributors I'd forgotten about and don't include kernel.h -- it
Update NNSVM. Don't count on those special functions that were in LinearKernel.
Oops, that single warning apparently makes the build unstable...
Move files to .hpp and .cpp. Comment LMetric and MahalanobisDistance well.
Fix a couple loose ends I didn't before.
Fix includes and const.
Update name of lmetric.h to lmetric.hpp.
Update name of lmetric.h to lmetric.hpp.
Document NeighborSearch class.
Put these things inside the gmm namespace.
Document the SortPolicy classes; we will use the NearestNeighborSort class as
Remove fastlib repository (fake commit during svn to git transition).
Move mlpack/trunk/ to root of repository (fake commit during svn to git
Remove mlpack conf; it will live in its own repo (fake commit during svn to git
Hide parameters inside of a namespace to help avoid collisions (#74).
Hide PARAM declarations inside a namespace to help avoid collisions (#74).
Insane commenting of everything. I think the PARAM_* macros should be split
Implications of renaming io.h to cli.hpp.
Make sure we include cli.hpp, not io.h.
Move log.h to log.hpp, log.cc to log.cpp, and comment those files.
Implications of log.h -> log.hpp change.
Hah. That last important file need to change. Yeah, that one...
Move some more files to .hpp or .cpp. Place Option and ProgramDoc classes
Move files and then make sure documentation is created correctly.
Uh, I forgot a few things. Stupid Ryan.
Comment the rest of the things in the io directory and move the files to .hpp
Use BOOST_REQUIRE_SMALL instead.
Move spacetree.hpp to binary_space_tree.hpp (better name) and comment it all.
Update includes of binary_search_tree.hpp.
Reformat files in the math directory; comment them, and adhere to some new
Changed a filename
Changed filenames
Using math_misc.hpp not math_lib.hpp.
Update names which were missed due to svn merges and my own failure to check the
Bank error in your favor. Collect $100.
Seriously, I didn't check this in?
Add extra Mat code to load a transposed matrix. The patch has not yet been
Don't include Armadillo directly; just include core.h.
Use CSVs not ARFFs. Transpose the dataset upon loading.
Transpose matrices upon load
Why was it named .arff when it was a .csv?
That's odd, I didn't properly convert that one to CSV.
Use overloaded mat.save() and mat.load() functions.
Different ordering for includes. Include armadillo in arma_extend.h.
Corner case: last_coordinates_ may happen to be initialized to what the user
Require Armadillo 2.0.0 minimum, so we have CSV support.
Stupid idiot Ryan should not have checked that in
Stop using TextWriter. This breaks already broken code. Waiting on resolution
Remove col/ and file/ since they are no longer used.
Don't include textfile.h because it doesn't exist.
Add data::Load() and data::Save() methods to wrap Armadillo functionality.
Re-add data directory.
Add load.hpp and save.hpp to default includes.
Use data::Load and data::Save. This should fix our tests being slow.
No need for duplication
Use BOOST_REQUIRE_CLOSE instead of just plain assert().
Fix compiler warnings so build is stable. This whole output file business still
Update mog functions, eventually to be renamed GMMs. Work in progress -- not
Add test for MoGEM.
Someone owes me some food for this... well... if it's the bug.
vec = double resized the vector to size 1.
A better test, but it's not quite working for some reason.
Set intercept to 0 for test debugging.
commit 6638058bc5e86350361cbadac963fbc91747dc59
Remove the extra load() stuff that was not the right choice in the end.
No more contrib/.
Fix documentation a little bit. We want the bug list; we don't want .svn.
Use new load().
Update all tests to new formatting standards and make them all .cpp not .cc.
Add HMM test. A bunch of stuff does work.
Modify HMM code. We'll make a new class, HMM<Distribution>, which will serve
Change the names of a few methods, and implement supervised training/estimation.
Add test for supervised transition and emission matrix estimation.
Loosen bounds on test because the variance in the test is a little more than I
Now there's a tricky corner case. If the random value is 1, then that
Implement Generate() functionality.
Widen error tolerance to more reasonable levels (determined empirically).
Add function to calculate log-likelihood.
It's tired and I'm late, so I make stupid simple errors like this.
Add one more test for Generate(). The tolerance is a bit higher than I would
Test HMM::LogLikelihood() for the discrete case.
Comment Estimate() a little better and provide a convenience overload.
Use exact tolerance for probabilities, because it's harder to estimate smaller
Begin construction of Distribution classes so that we can generalize the HMM
Oops, I named a file wrong.
Update CMakeLists to include new files.
Flesh out DiscreteDistribution class entirely. Inline functions in class
Add tests for DiscreteDistribution. These all work.
Fix compiler warning.
Make normalization safer; avoid division by 0.
Add simple constructor and then make sure that every constructor normalizes the
Make sure the distribution is normalized.
Test that the distribution is normalized after construction.
Abstract away from the discrete case. Now, everything depends on Distribution
Use new HMM syntax, with DiscreteDistribution instead of int.
Document the HMM class more effectively.
Use a default template parameter for HMMs.
Move mog to gmm and update CMake configuration.
Remove MoGL2E. That can be implemented some other day.
Move GMM test to where all the other tests are.
Add an overload of phi() which can do multiple data points at once; this way, we
Remove debugging output.
Rename MoGEM to GMM. Make cond_prob calculation a lot faster (but there are
Why did this ever pass any tests? I am officially confused.
Format things just a little better.
I am really frustrated by tests that don't always have a deterministic outcome.
Update GMM code. It should be a little faster training, but it is still too
Compile GMM.
Flesh out main executable for GMMs.
Tests for GMM. Multivariate multi-Gaussian training tests included (that was
Const-correctness, yo.
Fix some warnings I inadvertently introduced.
Add Gaussian distribution class.
Compile Gaussian distribution class.
Tests for GaussianDistribution class.
Why is this file here?
#162: use log-likelihoods instead of direct probabilities because direct
Add a first test for a Gaussian HMM.
I accidentally had not generalized to the general observation case.
Add test for Gaussian HMMs where we are training for both the labeled and
Widen tolerances for unlabeled training.
Test Generate() with a Gaussian HMM.
Make sure the state probability makes sense.
Don't use srand() in tests, so that the results are reproducible.
Move distance functions and metrics into metrics/, and update the build
Update kernels to metrics (where applicable).
Update kernels to metrics (where applicable).
Fix style as per #153 and name local class members as per #118.
Update style for #153; it was not completely done.
Adapt style per #153.
Fix formatting as per #153.
Remove test file, and fix formatting as per #153.
Update style as per #153. Also, we didn't need the test here anymore.
Fix formatting in tests/ as per #153.
Format EMST as per #153.
Comment FastICA code as per #153. Remove a couple unused functions in
Change filenames as per #152 and fix formatting as per #153.
infomax_ica.h is now infomax_ica.hpp.
Remove kernel PCA before Ajinkya's version, since Nick's won't be used.
No more kernel PCA = no more kernel PCA test.
Update formatting of linear_regression to reflect decisions made in #153.
Move filenames to .hpp and .cpp to help finish #152, and fix style in accordance
simple_nbc.h is now simple_nbc.hpp.
Change NCA filenames according to #152 and change style according to #153.
nca.h is now nca.hpp.
Rename files to .cpp and .hpp in accordance with #152, and fix style to be in
neighbor_search.h is now neighbor_search.hpp.
We won't use Nick's implementation of ridge regression; we'll extend
Remove RidgeRegression test since we aren't using that implementation anymore.
Change to .hpp.
Change name to .hpp.
arma_extend.h is now arma_extend.hpp.
No more regression.
arma_extend.h is now arma_extend.hpp.
Use long doubles for comparison (compatibility with older Boost UTF).
Style MVU as per #153 and move to .hpp and .cpp as in #152.
Fix formatting of NNSVM code (#153).
These methods are unmaintainable and will have to be re-implemented.
Remove SVM test and NNSVM test.
This is not used anymore.
Move core.h to core.hpp. Fixes #152.
Move K-Means to be its own method.
Make KMeans into an actual class. It now supports "overclustering".
Add test for KMeans.
Add KMeans test and comment out GMM test since its API has not yet been adapted
Don't build GMMs because they don't yet work with the new KMeans class.
Add test for MinDistance identical case.
Add a test for the identical case for MaxDistance().
Adapt to new KMeans API.
Start compiling GMMs again.
GMM tests work again.
Absolutely minor formatting issue fixes; use BOOST_REQUIRE_CLOSE instead of
Abstract some features of KMeans into template policy classes.
Adapt KMeans to new policy-based API.
Test the different policy features of KMeans.
I thought I was helping, but it turns out I just made things worse.
You have to zero the counts first!
A better way of calculating the covariance, more akin to arma::cov.
Executable for K-Means. Celebrate!
Main executable for PCA. A couple little tweaks to the PCA code here and there.
A couple formatting fixes after Ajinkya's fix for #165.
A couple more formatting fixes.
Make sure the covariance matrix is positive semidefinite.
Add another test case and simplify the first test case; the second test case
Update timers.hpp and timers.cpp to conform to formatting guidelines (and fix a
Change API to newer standards for HRectBound and BinarySpaceTree. Fix some
Make Range adhere to new formatting and naming conventions.
Update uses of BinarySpaceTree to conform to new API.
Update tests to reflect API changes.
I have truly gone full style Nazi. But hey, now the variable naming conventions
Improper use of regex leads to over-confidence about code compilability then
Revamp L-BFGS code to remove CLI from its insides. Naming convention fixes,
Fix const-correctness of GetInitialPoint().
Remove FastICA because Nishant will be implementing RADICAL instead.
Don't compile lin_alg_test while I think of where to put that code.
Fix for integer parameter.
Move FastICA linear algebra utilities to core/math/ (pending rename).
Run the linear algebra test again since it's now in a different place.
Remove unused PARAM_*.
Overhaul API for NeighborSearch (it probably is not complete) and remove
Update tests to conform to new NeighborSearch API.
Accidentally committed this minor change.
Remove CLI parameters from LBFGS.
Remove infomax_ica since it will not be released.
Update comment to be more accurate.
Minor tabbing fix.
Remove InfomaxICA test.
Remove Print() function in accordance with #164.
Formatting fix, and prune CLI from the internals of DTB.
Prune CLI from the internals of DTB.
Put the statistic class into the tree namespace.
Add (as-of-yet) untested Range::Contains(const Range&).
Add RangeSearch to the list of methods we have.
Add tests for RangeSearch; they are comprehensive (pretty much).
Add Dimensionality() function to distributions; use arma::mat and arma::vec
Adapt test to new distribution API.
Adapt HMM to only use arma::vec as observations.
Adapt HMM tests to new API.
Compile RangeSearch.
Fix sanity check to actually check things correctly.
Add Estimate(const arma::mat&, const arma::vec&) so that this class can work as
First simple test for GMM::Estimate(const arma::mat&, const arma::vec&).
Move .h to .hpp and .cc to .cpp. We don't need dummy.cc anymore so it's
Compile LARS.
Big API changes for LARS. Move things into the constructors; rename internal
Add GMM test case for training multivariate Gaussians in the setting where
It helps when you actually implement the stupid function instead of being an
Issue a warning when an empty GMM is created.
Test GMM::Random().
Actually, make that debugging only...
Test HMMs with GMMs; a simple Predict() test. Still need Estimate(),
Don't use srand() in a test case.
Don't use srand() in test cases.
Add -NDEBUG flag.
Transpose before adding rows.
Misspelling of option.
For some reason, this caused a segfault with -O2. This needs to be looked into.
Yeah, break everyone's build by requiring 2.4.0. It's for a good cause though.
Add sparse support which can be patched into Armadillo if necessary.
Convert u32 to uword for 2.4.0.
Templatize the matrix type.
Abstract-ize HRectBound to accept arbitrary types of things.
A typedef so other types that depend on the matrix type can use it.
We can use regular .col() here since we abstracted away arma::vec.
Stop using unsafe_col().
Refactor API to be consistent with RangeSearch.
API changes.
These aren't necessary with Armadillo >= 2.4.0.
Too much noise means I start doing things wrong.
I had been approaching the wrong solution to the issue because they keep
Copy code over from arma-sparse branch.
Retry the API change. This time it works...
Simpler swap_cols() and SpValProxy::operator=(SpValProxy&) to make it work.
Why does this fix the test? I don't know, but there's not complete time to fix
Allow sparse vectors to be passed to metrics (this should get a bit of speedup).
Abstractize vector type.
Abstractize k-means so it can use sparse matrices.
Explicit conversion to mat.
Centroids should be sparse, too, if we want them to be.
Support SpSubview proxies.
Use a const reference internally in SpSubviews.
Test sparse K-Means.
Unused variables.
Abstract-ize matrix type used for NCA datasets. The covariance matrix should
Sparse NCA doesn't actually make sense.
Abstract-ize NBC to allow sparse matrices.
Clean up CLI formatting... for like the fifth time.
Document EMST better.
Oops, I need a <>.
Make statistics useful again.
New Statistic API.
New Statistic API.
Restructure test.
Refactor and clean up EMST code.
Refactoring of EMST/UnionFind API.
Update for transposition of output.
Clean up CLI output again and again. Then change how Timers works because it
Make it how it was before.
Allow compilation with -DARMA_EXTRA_DEBUG.
Compile libmlpack.so not libmlpack.a.
Comment things a little better, and rename one of the timers.
This was not an input parameter.
Change in HasParam() changes a couple things in this test.
Move io/* to utilities/* then utilities to util (shorter, simpler name) and
-v == --verbose
Allow a GMM to be saved and clean up documentation.
Minor documentation fix for the namespace emst.
Documentation fixes for GMMs and removal of now-unnecessary README.
\bandwidth is not valid LaTeX... thanks regex...
Two asterisks, not three. What is the meaning of life?
Last run of modifications for EMST documentation.
Expand the example for the GMM. This documentation should be done.
All these files are unnecessary because I re-implemented HMMs.
Update documentation for HMMs. Documentation should be done for this class.
Don't build these targets.
Remove these executables because they don't work anymore.
Better documentation for K-Means.
Fix #174 and another bug in the main executable.
Fix segfault.
Copy test data to the right place after building the test.
Standard header include protection.
Split math_misc.hpp as per #143.
Change variable names to match code specifications and mark a couple functions
Add license and copyright to satisfy #175.
That's embarrassing, I forgot the name of the guy who opened the ticket to make
Ignore some other things that we hadn't previously been ignoring.
Move kpca to kernel_pca; clean up the code to match formatting standards (okay,
Clarify program name.
Redo LinearRegression API and put it into the regression namespace (not
Namespace and API change for LinearRegression.
Fix a bug which was overwriting memory and may be causing that segfault I am
Refactor and comment NaiveBayes a little better.
Fix bug and better warnings.
Document NCA.
Not sure why I need to raise the tolerance... maybe something worse is wrong?
Redo API for NeighborSearch for the last time and go over documentation.
Change formatting of RADICAL code and redo the documentation a little bit to
This caused a problem for release-mode, so maybe this is the instability in the
Reset the tolerance to normal.
Format LARS a little better and give good program documentation.
Update LARS test.
No longer need l here.
I can't reproduce this error anywhere! Is something wrong on the build server?
Clean up warnings.
Version .so at 0.99.0.
Remove unnecessary 'normalizer' variable and add accessor for gamma. No mutator
Use accessors and mutators for math::Range.
Update tests to use accessors and mutators for math::Range.
Add accessors and mutators for AugLagrangian and L-BFGS. Change int to size_t
Refactor BallBound API and clean it up.
Change in BallBound API.
Some SpMat bugfixes.
Document timers and CLI a little better since we changed how it all works.
This isn't used anymore...
Add some useful documentation.
Better documentation. Now we have a quick guide to MLPACK.
Remove a few warnings.
Pretty poor implementations of min() and max() for sparse matrices.
Clean up BallBound code; now, expand things in batch because that's better.
Clean up warning, use Info instead of Debug.
Clean up MVU code and add a main executable to it.
Make sure that Doxygen actually picks up the guide we wrote.
Inline math::Range.
Use Boost random number generators; account for API changes in 1.47.0.
Require boost::random and link against it.
Stop using rand() and use Boost random numbers.
Explicitly specify namespaces.
Give a few specializations for vectors, and remove using directives.
Give direct access to discrete distribution probability vector.
Update to new direct-access DiscreteDistribution::Probabilities() API.
Clarify error messages, and actually assign the parameter to what is read for a
Normalize vectors because Probabilities() doesn't do it anymore.
Add main executables for HMMs.
Explicit namespace usage.
We have a few more executables now.
Implement operator|= correctly.
Fix use of uninitialized variables.
Utilities for loading/saving HMMs; to be deprecated later.
Move distributions to core/dists/.
Add CMake configuration.
Fix formatting for L-BFGS.
Fix formatting for AugLagrangian and associated test functions.
Fix braces.
Fix comment.
Change name of box().
Boost <= 1.41 did not have a separate random package.
Search correctly for Boost.Random. It did not exist separately until 1.46.
box() -> Box().
Fix >= Boost 1.47 issues.
box() -> Box()
Smarter linking of MLPACK against Boost.
Fixes for old Boost.UnitTestFramework.
Don't run test cases that don't work because the code was never finished.
Fix two warnings and some style.
Add RandomSeed() function to set the random seed, which is always a good time to
Use uint32_t because that's what the class uses internally.
Hey, cool! A warning solved a bug.
WTF SVN? I update, you give a conflict, and when I resolve it, you drop the
Add option for random seed (for #182).
Add support for --seed to HMM executables (where necessary).
Add --seed support for K-Means executable.
Minor spelling fix.
Set the standard seed (srand()) also, because Armadillo is likely to use that,
Weird, these aren't necessary.
Make documentation more the same-like. You know?
Add a tutorial for NeighborSearch. That took a little while...
Add an actual page for the tutorials.
Some formatting fixes. We have lines longer than 80 characters but that is
So that we get that nice hyperlink.
No -Werror for now (the build server gets angry, gcc doesn't have to).
Fix some errors present on older gcc versions.
No need to link against LAPACK or BLAS; Armadillo does that.
Install binaries in the proper location.
Wait, it's not an ugly hack anymore (it was before, then I changed it and forgot
Add 'make test' command. This should make the build fail if the test does not
Add 'make doc' command, but it does not yet install the documentation (that will
Rename project to 'mlpack' (so we install documentation to
Higher tolerance for Laplacian kernel.
Don't use GNUInstallDirs. Assemble /usr/share/doc/mlpack/ by hand (it's not so
Don't install Doxygen documentation if it was never built.
Haha! Other people should be able to make tutorials too!
Fix scoping issues. Stupid Ryan!
Refactor AugLagrangian for better use by other classes. AugLagrangianFunction
This will hold an optimizer for low-rank semidefinite programs, formulated by
Basic implementation of LRSDP. Not yet tested.
Don't set any RPATH.
Revert RPATH change. We have to build with the RPATH and strip it at install
Actually write the "correct" installation commands, so that RPATH gets stripped
Add operators for SpSubview.
A script that can turn our output into man pages. This is for packaging, but
No preview in an automated setting...
Script to make all man pages.
Make the directory if it doesn't exist.
Force gzip compression; make sure it is not interactive.
Make rules to generate man page documentation. This is goodliness.
Apparently, when I wrote this, I did not understand how floating point numbers
Temporary work check-in so I can work somewhere else.
Temporary work check-in so I can work from elsewhere.
Change documentation a little bit to prevent man macro error (hopefully).
Fix spelling error.
Wow, awk is crazy. This fixes warnings in the troff output given by txt2man.
A few changes to the implementation of LRSDP. Still does not quite work yet.
Limit on number of iterations, and set the first lambda value right for LRSDP
It works! I can't believe it works.
Don't do extremely simple LRSDP test; it needs a different first Lagrange
Allow setting of random seed for RADICAL.
Fix a few warnings for unused variables that I introduced.
Add the dataset we work with.
Allow two modes of constraint matrices. Not yet documented.
Add tests for two other Lovasz-Theta problems. hamming6-4 isn't converging
Update for new L-BFGS API.
Revamp L-BFGS API, moving around where the maximum number of iterations is set
Revamp the AugLagrangian API to deal with the new L-BFGS API, and take a
A quick hack to make the tests faster. This'll go away when I redo the LRSDP
Revamp NCA and MVU, which use AugLagrangian and LRSDP, respectively. MVU is not
Don't link range_search_main.cpp into MLPACK; it adds unwanted CLI options. And
Further refactor AugLagrangian API to make it simpler.
Refactor LRSDP API for ease of usage.
Clean up LRSDP test and add a dataset which we are not using (but the test is
Just so it compiles for now...
Let's not set sigma to a value which ensures the algorithm will never
Fix out-of-order initialization warning.
Add RandNormal() and fix some const-correctness semi-issues.
Misplaced space. The horror!
Initialize StatisticType objects in the root node too.
A few fixes so that things can compile with older Boost.Test versions.
Some changes; use M_PI instead of math::pi() (for consistency across all MLPACK
Move to range_search_main.cpp and clean up executable.
A couple changes to the kernel PCA test.
Clean up some comments and the sanity check on the dimensionality should be the
Put down the crack pipe, Ryan.
This is a copy of the Gaussian kernel... oops...
Remove exponential kernel from sources.
Some cleanup for kernels.
No more ExponentialKernel.
An actual main executable and some implementation tweaks for speed.
Some formatting fixes.
Add --scale and --nocenter options.
I had the options backwards; also clarify documentation.
Add --scale and --nocenter options. Also center by default for PCA.
Helpful note pointing to other documentation, so we don't need to include
Slight change because CLI outputs differently now.
Remove unnecessary citations and change formatting of citations with respect to
Remove citations from -h output.
Remove citation from -h output.
Remove citation from -h and put @code around it in the RADICAL documentation.
Fix references in tutorial; rewrite into a little bit and clarify some
Forgot two references.
Fix references.
List linear regression tutorial.
Credit where it's due. I might be missing a name or two...
Mistype found.
Add a range search tutorial. Should be done...
Add range search tutorial to list of tutorials.
That isn't a correct Doxygen comment...
Initialize LRSDP A and b vectors to the correct size at construction time,
The sparse A matrices should be able to have a value.
Changes according to the changes in the LRSDP API.
Hey, so, it turns out when you find the package, you've gotta add the include
These aren't necessary any more.
Some changes to mvu. Not 100% sure if it works yet.
Some changes that had been forgotten.
Unpack tar.bz2 for Nishant's sparse coding tests.
Maybe it works, but I'm not totally sure.
Three new methods for trunk.
Add local_coordinate_coding and sparse_coding to man rule.
Untested Windows code needs to not be untested...
Fix #207.
Install range_search executable.
Use in-house random functions, not drand48().
Make CMake configuration better by linking directly to the library locations, not just the library. This is for Windows compatibility.
Reformat CMake configuration file. Only use -Wall and -Wextra on GCC-like
We shouldn't provide these ourselves; CMake 2.8 does that already.
Windows #defines min and max; undo these defines so we can use std::min() and std::max().
More typenames, required by VS2010 but not by GCC (for some reason).
Only give stacktraces on Linux boxes; Windows doesn't have execinfo.h or cxxabi.h.
Fix apparently untested Windows code.
No execinfo.h on Windows.
Eliminate ambiguity in a few function calls.
Require FORTRAN because FindLAPACK requires FORTRAN.
Wait, we don't even need LAPACK. That comes through Armadillo.
Turns out not every version of CMake ships with this...
Special handling of Boost linking properties for Visual Studio. This was necessary for me to make things link correctly.
Implementation of round() for C99-deficient compilers (MSVC...).
Use boost tgamma and include that round function we made earlier.
Link to direct location of unit test framework library.
Various fixes for Windows compilation.
Be a little pickier with how we build on Windows. Static library because creating a DLL correctly would be a nightmare.
Fix #210. Stupid error...
Generate Doxygen documentation with 'make doc' only in out-of-source build
Make timers multi-run.
Test multi-run timer functionality.
Look for possible dependencies of libxml2.dll, to issue a warning to the user in case they don't exist.
Link against LAPACK and BLAS on Windows because Armadillo doesn't automatically do it.
No colors on Windows because command.exe doesn't recognize ANSI color escape sequences...
Patch by andreasl: no definitions of promote_type<u64, ...> are necessary if
Patch by andreasl: change u32 to uword (the generalized Armadillo type, which
Oops, I did screw it up.
I think that some of the promotions I had written are actually invalid. For
It makes no difference in reality, but don't define is_supported_elem_type<u64>
Define timersub() before it's used on Windows boxes. For some reason VS2010
Use Sleep() on Win32 systems. This isn't tested yet -- but I'll do that in a
Greater than or equal to -- because some systems are very precise.
Require version of libxml2 to be at least 2.6.0 (which is dated late 2003... so
Search for iconv.h on Windows systems.
Artifact from pthreads which isn't used anymore.
Add GMM::Probability(arma::vec, size_t) as part of #212.
Test GMM::Probability() (both overloads).
Add a Classify() method.
Test the new Classify() method.
Increase tolerance a little bit so the builds don't fail so much.
I hate test tolerances so much.
Undo accidental test compilation commit -- we like all the tests.
Add to contributors
Handle a case where the step size ends up being 0 but the gradient is not yet
Clean up some man page warnings.
Use Log::Debug instead of cout for debugging output (maybe it should be Info?).
Declare the function before we use it.
Refactor GMMs so that you can use any clustering method you like. The default
Use GMM<> not GMM, because it's now a templated class.
Rewrite GMM tests to use GMM<> not GMM (because it is a template class now).
The fabled GMM-HMM training test. The hardest of all tests, only the strongest
Hackery necessary for sparse support using Armadillo 3.0.0 or greater.
Include new traits.hpp file.
Workaround for Armadillo 3.0.0 bug.
Fix ambiguity error under Armadillo 3.0.0.
Pass one: comment grammar Nazi and fix code style issues.
Pass two: const-correctness (mostly) and use size_t instead of arma::uword.
Missed a couple uwords.
Rename some variables in the class. Not done yet...
Update tests to reflect new method names.
Fix longer-than-80-character lines.
Fix longer-than-80-character line.
First pass: style. Fix a memory leak or two too.
Fix namespace ambiguity.
Take care of FittingType when we are passing in means, covariances, and weights
Handle Boost 1.33 Random library correctly. I am not sure how far backwards
Fix preprocessor ifs for Boost <= 1.39 Random API changes.
Make ourselves compatible with older versions of Boost.Test.
We need to actually get the version number before we check what it is...
Zero the memory before we start adding to it.
An implementation of cover trees. It is not yet polished, and the debugging
Add two tests for the CoverTree class; a simple test and a big (random) test.
Add NumChildren() and Child() to BinarySpaceTree for compatibility.
Fix warnings I introduced. Oops...
Comment the CoverTree implementation a lot better. Still a few things to do...
Remove unnecessary debugging output from test.
Regresion is cool, but this method is regression.
Refactor LARS. Fix comments, remove unnecessary methods, and consolidate
Don't use a pointer for LARS objects; no need to do memory allocation on our
In fact, remove the line entirely.
Refactor in accordance with new LARS API.
Allow arbitrary metrics to be used in the construction of the cover tree.
Test an alternate metric construction of the cover tree.
Fix misleading documentation...
s/IO/CLI/g wasn't a good idea.
Allow template parameter class to specify which point should be chosen as the
Add NumPoints() and Point() to BinarySpaceTree. Maybe Count() and Begin() could
Give better debugging output.
Tabs to spaces, and return a reference, not a pointer.
Add a single-tree depth-first traverser. It is not as fast as it could be.
Add the NeighborSearchRules class, which defines how the
Ack, how could I violate my own coding style guidelines?
Add the very similar SingleTreeBreadthFirstTraverser, meant to be used with the
Modify the API of BinarySpaceTree to include a few more methods. Starting to
Modify CoverTree API towards a more standard API. It can be used with
Update our traversers so that they don't consider self-children. I am not too
Update API to use TreeType::MinDistance() because other tree types may not have
Use the tree's preferred traverser type.
Fix some formatting and style issues, and then add a test for nearest-neighbors
Remove unnecessary debug output.
Add a dual-tree depth-first traverser.
Save just a little time where we can.
Include statistic.hpp (so we have EmptyStatistic).
Add dual_tree_depth_first_traverser.hpp to build list.
Add an option to use cover trees.
Add implementation of rules for dual-tree search.
Use DualTreeDepthFirstTraverser for naive and dual-tree calculations, and remove
This bothers me a lot more than it should.
Make this an iterative implementation.
Well, that would break everything...
Add DualTreeBreadthFirstTraverser (at this moment, not rigorously tested).
I didn't do this right; I forgot about the "UpdateAfterRecursion" step and broke
Correctly handle cases where implicit nodes are created.
Add a preferred dual tree traverser.
Add preferred traverser and dual cover tree traverser (which doesn't prune at
Add rules for cover tree search. This breaks the nice abstractions I was trying
Add a dual-tree test for cover trees.
Add directory for implementation of MaxIP. I think it needs a better name...
Remove debugging output.
Add the IPMetric, which is the "inner product" metric which calculates the
Add rules for the MaxIP single-tree search.
Add MaxIP class.
Add CMake configuration so MaxIP gets compiled.
Add maxip to project build.
Add simple first test for MaxIP.
Clarify error message; k can be equal to the number of points.
It helps if the conditional is right, too.
Give number of prunes.
Add maxip executable.
Don't get it backwards...
Add template specalization for linear kernel.
Avoid double-evaluation of base case.
unsafe_col() is faster.
UL and ULL extensions for older GCC.
Reimplement single-tree search. It's faster now.
This file doesn't exist. I didn't need it.
Ensmallen and randomize.
Initialize products to DBL_MIN.
Use unsafe_col() 'cause it's faster.
Rewrite to only use one queue. Not very happy with this implementation.
Add a kernel which I'll remove later. I don't like it...
We can do polynomial kernels too.
Check in modifications.
Update kernels in ugly ways that need to be removed later.
Needs to be the square root, not actually K(q, q).
Put ugly global variable in so it compiles. This will be cleaned later...
Consider queryProducts kernel evaluations too.
Don't used squared distance in tree construction.
Revamp breadth-first descent to consider tree levels so it is the proper
Count kernel evaluations.
This test does not compile with Armadillo 3.2; I have not yet had a chance to
Work for older CMake versions (2.8.2) and finding older Armadillo versions.
Halfway transitioned to newer implementation, which does not try so hard to
Rewrite swapping code.
Some slightly ugly additions -- but which give an order of magnitude speedup
Relax the separation constraint to include equality (in accordance with the
Store furthest child distance and furthest descendant distance. This can allow
Fix a couple bugs in furthest child and descendant determination.
No far set in root node.
No far set in root node.
Parent distance is the interesting one to track, not furthest child distance.
Add two more kernels. They need to be parameterized.
Clean up cover tree implementation a little bit. Allow instantiated metrics
Refactor and clean epanechnikov kernel.
Remove static Gaussian kernel hack.
Best not to promise functionality we might never get around to.
Remove the no-offset kernel; it is not useful and was a hack for a deadline.
Include new files.
Fix top-of-file comments.
Rewrite triangular kernel with parameters.
Check in mess of MaxIP code which is being cleaned little by little...
Test modified for new MaxIP API.
I don't believe this is a valid kernel.
Update documentation slightly.
Finish refactoring for each kernel type.
A couple of files were not included.
Some code cleanup.
Code cleanup; don't use namespace arma (since that's done nowhere else) and
This was being passed in backwards.
Modify LARS API to accept non-transposed matrices. This is easier on the
Adapt for new LARS DoLARS() API.
More refactoring; remove nActive because it isn't necessary, and include
Changes to DoLARS() propagating to here.
Changes to DoLARS() propagating to here.
Change DoLARS() to more descriptive and less awkward Regress(). Minor code
DoLARS() -> Regress().
DoLARS() -> Regress().
Apparent typo in the test cases meant one combination was not being tested.
Changes to main executable in accordance with the modified API.
Add option allowing user to specify if they want the data transposed on input;
Tests for new options to data::Load() and data::Save().
Clean up LARS executable.
This check changes because we're loading X and not transposing.
CLI::GetParam<bool> seems to crash, and, add a timer.
Add some timers for loading and saving operations.
Clean up documentation slightly.
Stop timer for early exit.
Clean up comments for no good reason.
Refactor SparseCoding to initialize the dictionary as a template parameter.
Change tests to respect new SparseCoding template parameters.
A couple of formatting fixes.
A couple more tutorials now exist.
Clean up comments, and store a reference to the data, instead of copying it.
We don't need to set the reference -- this line is now implicit.
Rename DoSparseCoding() to more flowing Encode().
Minor style changes.
Fix some syntax errors I introduced, and print the matrices. The test does not
Formatting fix, and handle things a little more carefully.
Clean up code. Use std::pow(x, 2.0) not x * x. A couple of formatting fixes,
Stop using activeAtoms because it isn't necessary (minor speed boost). Clean up
Avoid a matrix copy for matActiveZ and potentially speed up gradient calculation
Clean up main executable. Avoid unnecessary copies.
Fail on failure to load dictionary.
Avoid unnecessary initialization of dictionary when the user passes a dictionary
Clean up style violations.
Clean style violations in main executable.
Template LocalCoordinateCoding to accept different kinds of dictionary
Update for new LCC API, and fix style violations.
Make OBJ_TOL and NEWTON_TOL parameters to the methods.
Change matX to data, matD to dictionary, and matZ to codes.
Update for new API with better matrix names.
Clean up formatting of output, and stop using arma::uword (prefer size_t
Oops, this isn't necessary anymore.
More consistent comparisons
Change DoLCC() to Encode() and some cleanups and fixes in Encode(). Reduce
Fix inaccurate comment.
Update test cases for different cosine distance.
Comment out testing procedure for now because it doesn't work (yet).
Clean up and optimize code.
Move RemoveRows() to the linear algebra utility section since it's used in more
Include linear algebra utilities.
Move RemoveRows() out of class definitions.
Remove extraneous spaces
Minor spacing and formatting changes.
Cleaner calls to .rows() as opposed to .submat() with all those arma::span
Tests for RemoveRows().
Be pedantic about namespaces.
This causes an ambiguity error (mlpack::math or arma::math?) on gcc 4.4.x.
Set limit on maximum iterations so we don't spin forever.
Better error messages (more descriptive, less awkward).
Severe cleanup of executable, so it actually works again.
Use timers internally, not externally.
Use timers internally, not externally.
Fix unclosed '
Fix doxygen documentation (forgot a @code).
Use log negative error to prevent calculation overflows (a first step towards
Update test API to use LogNegativeError().
Simplification of expression
Yeah, this is simple enough to inline; probably a better choice.
This function can be const.
This function can be const.
First shot at overhauling FindSplit_(). Break deep nesting of if/for by
Fix lots of formatting issues in DETTest tests. Stop casting to/from float/long
Minor style fixes and const-correctness fixes.
Uh, I forgot the opening {
Further cleanup of casting issues.
Apparently unused file
Add parameters so user can specify objective and Newton tolerances.
Make objective tolerance parameterizable.
Switch to doubles not floats in main executable so it compiles.
Clean up casting for old Boost.Test versions which aren't very smart.
Rename FindSplit and its variables to names that adhere to the style guidelines.
Update test to modified API.
Fix corner case where found version is equal to the required version.
Add PSpectrumStringKernel to be used for maxip/FMKS.
Add tests for PSpectrumStringKernel.
Clean up FindSplit() and reduce API to only what is necessary.
Clean up test to adapt to new FindSplit() and SplitData() APIs.
Replace tabs with spaces. Remove unused variables. Use separate
Clean up constructors. Don't hand-allocate memory for minVals and maxVals;
Clean up test. Don't use 'new'/'delete'. Fix wrong index for TestSplitData.
Oops, there was one more 'new'/'delete'.
Clean up constructors; use initialization lists more exclusively. Also clean up
Use BOOST_REQUIRE_EQUAL(), and the function is now called WithinRange().
Further switching from cT to double. Later we will switch to all log error.
Use double instead of long double for Grow() and PruneAndUpdate().
Use double for ComputeValue(), and take a reference instead of a pointer; also
Update for changed ComputeValue() API.
Change API for ComputeVariableImportance().
Modified API for ComputeVariableImportance().
Stop using eT and cT for good. Change all variable names to adhere to naming
Refactor test to stop using eT and cT. Don't typedef MatType anymore, and
Clean up main executable file.
Further cleanup of variable names.
Convert all of DTree (with the exception of ComputeVariableImportance()) to work
Adapt tests to working in the log-space and update APIs accordingly (as they
Cleanup of dt_utils.hpp. Get rid of 'using namespace std' in dtree.hpp and
Remove templatization of density estimation trees (it wasn't necessary). It
...and make sure that the removal of templates is propagated to the test file...
Clean up CLI parameter names and then rename the executable to 'det' not
Fix std::pow ambiguity on older compilers
Fix pow ambiguity that I missed last time...
Actually, I got it backwards, I need pow(double, int).
This day is off to a great start
Remove unnecessary debugging output
Fix DET so it actually works. A few things here and there needed to be changed.
Disable volume regularization for the main executable for now.
Remove debug output which is unnecessary now.
Rename various parts of NMF to different names which line up more with the style
The API call for Apply() has changed slightly.
Allow objective tolerance option.
Fix tabs into spaces.
Restructure trees entirely. Each tree will have its own SingleTreeTraverser and
Add a few files we forgot, including the convenience include files which include
Change include files and APIs to use the new tree traverser setup.
Modify tests for new include locations.
Minor cleanup of NMF code; I think the residue should be displayed in
Add Score() and Rescore(), which will be used for a "new" type of tree traversal
Refactor BinarySpaceTree traversal to use Score() and Rescore() and thereby
Remove two now unnecessary files.
Oops, those files had to be removed from the CMake configuration too.
Oops, we need this check in there too.
Use unsafe_col() instead of col() for speed reasons (this makes a BIG
Ensure we check if we can prune before descending the query tree (this case is
Fix comment.
Give ourselves a way to force inlining.
Check if we can prune individual points before performing computations.
Speedups for math::Range().
Inline these functions for speed.
Force inlining of BaseCase() because that is extremely important to loop
Respect -s when combined with -c (single-mode cover trees).
Update single tree cover tree traverser to be smarter about recursion order.
Add new methods for finding the maximum or minimum distance to a point or node
Add new methods for calculating the best distances when the distance between the
Remove a few unused methods (LeftFirst() variants). Add Score() which accepts a
Rewrite the single tree traverser for the cover tree. It works, now it needs to
Fix spaces, and actually traverse to the left instead of just saying it and then
RandomAcolInitialization was modified to take a template parameter so now we
Heh... a template parameter is not an lvalue. So just warn the user and then
Oops, a small typo...
Tighten bounds on minimum and maximum distances because we already cached the
Revamp single tree traverser... again. For now it has debugging output.
Use L2 distance not squared-L2 distance because that breaks cover trees.
Get the conditional right. Only map things back like that if there was a query
Refactor single tree traverser again; don't use priority_queue which is slow.
FindArmadillo.cmake ships with CMake from version 2.8.5-rc1 onwards. So require
#223: I don't think we have ever needed to link Boost.Math anyway.
I promise, GCC, just this once, I'm smarter than you, really.
Split CoverTreeMapEntry into its own file since it will also be used by the dual tree traverser.
Some warning cleanup.
Seeming error; we just want the path, not the absolute filename.
Use correct L2 distance, not squared L2 distance in cover tree test.
Rewrite dual-tree cover tree traverser. The use of UpdateAfterRecursion() is
Remove unused CanPrune().
Be explicit and call std::log(double) because in some compilers (icc)
Heh... -h is already in use...
Safer handling of strings which may have spaces in them.
Missed one handling case
Fix floating point precision error which was causing issues only when compiled
Use base of 1.3.
Refactor and try to rewrite dual tree traverser so it is faster, but I don't think we're completely there yet.
Comment out debug output for now.
Comment out some debugging output.
Update bounds -- the tolerance was being exceeded (just barely).
Update documentation for the use of cover trees.
Change expansion constant to base (#240).
#240: Change expansion constant to base.
Must used square rooted distance to be a valid metric.
Use valid alternate metric in tests.
Fix a warning which was actually also a bug; Score() takes the base case evaluation as a third argument (optionally), not a previous score.
Update copyright file (should this be in a different format?).
New contributor
noinline wasn't suppoed to be checked in, oops.
Add one more contributor.
A few more modifications to the tree test
Propagate r13418 to trunk.
Trivially minor misspelling.
Add inplace_reshape() for reshaping matrices without doing anything to the data.
Add a test for inplace_reshape().
Document the impending doom which will certainly be caused if you use this
Complete sentences, yo.
Fix odd spacing and be unnecessarily pedantic with const-correctness.
That empty initalizer is implicit anyway.
Add constructor which automatically creates identity covariance, and don't check
Add tests for new MahalanobisDistance constructor.
Documentation fix, and tabs to spaces.
Documentation fixes.
Change template parameter names to be more in accordance with the rest of the
Change template parameter names to be more in accordance with the rest of the
Add TakeRoot parameter for use with LMetric<n, true>.
Test new HRectBound<n, true> functionality.
Make a stronger note that the LMetric without taking a root is not a valid
Update documentation for the HRectBound.
Ack, that's an annoying typo in a bad place.
Another annoying typo.
Update some documentation for clarity and coding standards.
Longer lines than 80 characters? Unthinkable!
Debugging output, not warning output. Oops.
Fix grammar in comments (utter pedantry) and a few style issues.
Tabs? In my application? It's more likely than you think.
First cleanup of code: adhere to formatting standards (mostly).
The mean was not being set to zero in the constructor where the documentation
commit cb8ecf1de096fe018ad388b496a3d84f9e6b6cac
Remove test, because it's just testing internal MLPACK functionality which is
Fix includes.
Utility to find MATLAB and the mex compiler.
Build rules for MATLAB bindings.
Build rules for the EMST MATLAB mex binding.
Makefile no longer necessary.
Finish CMake configuration changes for MATLAB bindings. This *should* break the
This comment is no longer necessary.
This comment isn't necessary.
Actually issue errors when mex is not found.
Clean up script a little bit, make it a bit friendlier.
Clean up configuration so that MLPACK will compile on systems without MATLAB.
Remove all the cmake_minimum_required() bits that weren't actually necessary
Further clean up script and handle things better when MATLAB does exist.
Use MATLABMEX_FOUND not MATLAB_MEX since CMake string comparisons are as stupid
Comments and cmake_minimum_required removed because they are not necessary.
Script to modify the file which controls the MATLAB default path to add the
Add MLPACK MATLAB bindings to the default MATLAB path.
Add new developer (Patrick did the MATLAB bindings).
Update copyright
Add DETs to the list.
Change name of output and update MATLAB binding accordingly.
Tabs? In your codebase? It's more likely than you think.
Slight reorganization.
Weird misspelling fixed
Stochastic gradient descent will live here.
Clarify documentation. L_BFGS is a minimizer.
Not yet tested -- but implemented in a few minutes. Turns out SGD is pretty
Modify namespace, and create CMakeLists.txt.
Add SGD, and add functionality to LBFGS test functions (which will probably be
Fix a few errors in these files.
Add a test function and make it work right.
Add a test for SGD.
Move everything into the mlpack::util namespace from mlpack::io or
Update to use mlpack::util namespace.
Fix formatting issues and prepare for new functions.
Fixes to use mlpack::util not mlpack::utilities.
Implement decomposable error function and gradient, then make NCA use SGD and
More parameters for NCA in accordance with the change to SGD.
Allow normalization of points, to prevent underflows.
Remove the normalization stuff... that is not the right way to do it.
Slightly smarter normalization strategy for large datasets.
Also support a random seed.
Stupid, stupid, stupid (#256)
Oops, I missed one utilities -> util change.
Explicit cast
Better default tolerance; 1e-5 is too high and may "accidentally" converge too
We were neglecting a term in the gradient...
Tests for the separable evaluation and gradient of the NCA softmax error
Add parameter to determine whether or not SGD is shuffled.
For real, I seriously considered anger management classes while hunting this one
Allow passing an initial matrix.
Change the way things are normalized.
No need to print the final matrix.
A better normalization strategy. And actually document how you make NCA work
Output the size when loading. How cool!
Rename in accordance with the submitted paper.
Update include location.
Rename all MaxIP files to FastMKS.
Rename MaxIP test to FastMKS test and update everything accordingly.
Remove sparse support from trunk.
Oops, don't remove inplace_reshape().
Only do sparse tests if sparse matrix support exists.
Add explicit constructors for sparse vectors, which are applied only when
No need to typedef u64 anymore; set size_t == uword by defining ARMA_64BIT_WORD
Update CMake configuration for removed files.
Fix links. #249
Workaround for the case of sparse matrices.
Bake in support for HDF5 -- if Armadillo has it.
Test HDF5 load/save functionality.
Fix a code error, fix build instructions to include package managers.
Actually, we can't just define ARMA_64BIT_WORD willy-nilly because it makes
Check for a 64-bit system where ARMA_64BIT_WORD is not enabled, and warn the
Issue a warning when a user tries to compile MATLAB bindings and they have a
Fix to work with older GCC versions in cases where math:: is ambiguous (stop
No need to warn if the MATLAB mex compiler is using a newer glibc than the
Use specific doubles for RHEL5 Boost compatibility.
Clean up MATLAB bindings for EMST.
Update AllkFN binding documentation to how it should eventually be.
Tabs to spaces
Very minor documentation change.
Add build rules, tabs to spaces, and remove unnecessary header files.
Update headers, tabs to spaces.
Remove unnecessary Makefile, change to appropriate headers, and add header
Remove unnecessary Makefile; add header comment, remove unnecessary headers, and
Remove unnecessary Makefile, switch tabs to spaces, add header comment block.
Error in comment
Clean up warning.
Fix documentation.
Manual tree constructor
Test for the manual constructor.
Update for cover tree API change.
Add option to compile MATLAB bindings.
Make recursion into the bindings optional.
Add a few new bindings and make the mex compiler required if compiled with
Move conditional on matlab bindings to matlab-specific subdirectory.
Put MATLAB_BINDINGS conditional at a lower level.
Add CMake configuration for this binding.
Tabs to spaces and correct includes.
Remove unnecessary Makefile.
Remove unnecessary Makefile, tabs to spaces, use correct includes.
Tabs to spaces, fix includes, remove unnecessary Makefile.
Fix includes, tabs to spaces, remove unnecessary Makefile.
Fix includes, remove unnecessary Makefile, tabs to spaces.
Add mutators for ParentDistance() and FurthestDescendantDistance() and fix a comment.
Add a method to get the furthest descendant distance.
Add a test for the furthest descendant distance.
Calculate queryNode.Stat().Bound() on the fly instead of just one time at
Don't use UpdateAfterRecursion().
Update comments for correctness to resolve #261.
Another comment cleanup.
Refactor NCA to take an optimizer as a template parameter, and default to SGD.
Update test for new NCA constructor.
Add option for optimizer type to parameters.
Add function for cover tree pruning.
Add Prescore() function which can be used to prune based off of parent
Use Prescore() to prune reference children without evaluating the base case.
Try to prune when copying reference maps.
Add new (hackish) rule for pruning while descending queries.
Fix NCASimpleDataset test.
Change formatting to fix style.
Clean up RADICAL code and add some more output.
Clean up documentation slightly for the case of slow runs.
commit 73b4c28c203fbdcb33f27755a22f26f0cfb513c2
Update to newest version (I mistakenly branched an old version).
Minor formatting improvements and warning fix.
Further implementation cleanup; build rules fix, and move test to test
Build LSH.
Add tests for LSH. They may be modified as time goes on.
Fix line widths.
Do not make copies of objects when printing to output.
Add copy constructor explicitly.
Add test for cover tree copy constructor.
Minor refactoring of BinarySpaceTree and addition of copy constructor.
Test for copy constructor of binary space tree.
Fix unsafe code in HRectBound; bounds can be NULL.
Refactor MRKDStatistic into three files (maybe a little overkill, I realize
Update for MRKDStatistic API change.
Flush status message to output before the size of the loaded matrix is
Some tricks to get u64/s64 support on more recent versions of Armadillo.
Add parent and Parent() so that trees can be traveled both down and up.
Add test for Parent() method in BinarySpaceTree.
Issue a warning (not a fatal error) if Armadillo's configuration file does not
A few changes to PrefixedOutStream and NullOutStream to deal with references
Refactor calculation of bound. It may need a further fix.
Don't use Prescore(); it doesn't work. Comment out for now (it may be removed
Add two new files to build.
Better calculation of bound. We could still optimize a little bit. Debug
Clean up string util files (no functionality change).
Oops; turns out there _was_ a functionality change...
Add traits for trees.
Add test for tree traits.
It turns out we can actually make the bound a little tighter, which I
Make GMM::Estimate() return double.
Update test for changed GMM API.
Clean up LSH code and add random seed parameter.
Add LSH to listed methods.
Remove using directive and extra whitespace.
Simple cleanups of RANN code.
Far less hackery is required for Armadillo 3.6.2.
Old versions of Armadillo are no longer allowed, so this code for Armadillo <
Fix warning.
Fully qualified name of var() for compatibility.
Exclude Armadillo 3.4 from K-Means sparse test because sparse var() was not
LSH requires resize() which is not present until 2.4.2.
Got the name of the macro wrong...
Armadillo 3.4 has some sparse bugs which cause this test to get stuck in an
Add history.
Abstract away the unmapping of points. Also fix a few bugs in AllkFN because
Test Unmap().
Forgot to test-build allkfn...
Change rowMajor parameter to transposeData parameter, which is set to true by
Update for changed LARS API.
Comment out checks for now; setting the random seed does not guarantee the same
Clean up tests; split into four (not three) tests, remove random seed setting
Move default arguments into declaration of function to make clang happy.
Cleanup for clang warnings.
Update style; remove _s.
Add Parent() function.
Update test so Parent() is also tested, and also update constructor parameters.
Reset parents correctly in the case of implicit nodes.
A few more examples to reduce the probability of error.
By default, take the root. Then it is a true metric. (L2-squared distance is
By default, take the root. L2-squared distance is not a metric.
Still use L2-squared distance by default; this needs to be fixed.
Don't use L2-squared distance by default.
Update tests because LMetric<2> is no longer the squared Euclidean distance.
Use the bound in the ICML paper.
Update to only use L2-squared distances (for now).
Simplify constructors; we don't use any of the odd ones.
Simplified statistic construction.
Adapt to modified statistic API.
Adapt to new statistic API.
Style changes
Oops, I did not realize there was an _impl file...
Update statistic API.
Update statistic API; for cover trees, actually call the initializer.
Don't use start anymore.
Clean up code a little, and allow returning of the metric associated with the
Remove empty constructor; store dataset; allow return of metric with Metric().
Add Metric() function, and refactor a little bit. The metric may be stored
Add test for Dataset() and update because the empty BinarySpaceTree constructor
The name of the executable changed. Update documentation accordingly.
Minor documentation change.
Add a readme. Readmes are good.
Fix bug in bound function for neighbor search. It is necessary to keep two
Add a new trait.
Allow returning of instantiated metric and centroid.
Add Diameter() function, which is useful for obtaining the furthest descendant
Test Diameter().
Cache furthest descendant distance.
All definitions should come before mlpack includes.
Make FastMKS work in the dual-tree setting. Hooray!
Clarify documentation significantly on Train(). Only allow setting of
Better debugging output for DiscreteDistribution.
Explicit namespace inclusion.
Clean up warnings.
Use custom FindArmadillo script, which will find (and link against) HDF5 if
Clean up output a little bit.
Update name of inclusion guard to fit with the rest of them.
Uh, this is a major problem.
Superfluous c_str().
Make Save() actually return a useful value.
Add Load() and Save() functionality for GMMs.
Test Save() and Load() functionality for GMMs.
Use GMM::Save() instead of a handwritten function.
Update coding standards.
Add perturbation to ensure that the covariance matrix does not end up empty (and
Add option for number of trials.
Add perturbation to covariances when necessary to prevent zero-valued covariance
Zeroes in any element of a diagonal of a covariance matrix can cause problems.
This should be informational output which is present even when debugging symbols
Do not divide by zero. This is important when there are outliers whose
Too many spaces.
Put in checks for non-invertible covariances after training; add perturbation to
This is necessary (apparently) until the FindArmadillo changes either get
Parameterize perturbation, tolerance, and maximum number of iterations.
Add parameters for EM algorithm, and also add parameter which adds random
Don't use a specified perturbation but instead a simple (but rather slow)
Remove perturbation parameter and allow specification of whether or not matrices
I think this warning can be somewhat misleading, so it should be removed.
Eek, I broke the build!
Use the same fix from GMMs to ensure that covariance matrices are positive
Allow parameterization of the tolerance of the Baum-Welch algorithm.
Add option for tolerance of Baum-Welch algorithm.
Slight documentation fix.
Minor formatting change.
Oops, this is not the accessor/mutator design methodology we are using.
Avoid issuing two warnings for one problem.
Add option to get the clusters back when the process completes.
Wrong index, pointed out by se7en7 in IRC
Fix bug in error checking, and make given errors a little more descriptive.
Better error checking, and, actually *use* the initial guesses if they were
Test the new functionality of k-means: initial assignments and initial
Add a new initialization method, which is an implementation of Bradley and
Add test for Bradley-Fayyad initialization (RefinedStart).
Add accessors and mutators, and mark function const (as it should be).
Minor formatting change.
Remove Pelleg-Moore support (as per #251). Allow the user to specify a file to
Allow Bradley-Fayyad initialization for k-means as initialization for EM
Oh yeah -- actually allow the user-specified parameters to *do* something...
I don't like how Doxygen does @see; this should look a little better.
Fix documentation for prettier @see results.
Remove ambiguous option
Name of argument changed
If loading fails, don't try to continue.
Patch for #272, pointed out by Marcus -- incorrect example.
Add directory for k-means tutorial.
Clean up DET tutorial significantly. It could still use some work -- but then,
Remove reference to alternate volume regularization example.
The last section shouldn't be a subsection.
The last section shouldn't be a subsection.
The last section shouldn't be a subsection.
The last section shouldn't be a subsection.
output_file is the option, not outputFile...
Stop timers if saving or loading fails.
Fix parameter names (asleep at the wheel?).
Change DistanceMetric to MetricType to be more in line with the rest of the
Wow, I spent a lot of time writing that. It's mostly checked for errors.
implementation of the \c EmptyCluster() function makes
Add directory for FastMKS tutorial.
It all has to be one big comment to be a page...
Refactor cover tree constructors into one CreateChildren() function, which saves
Widen tolerances on tests that seem to be failing often.
Widen tolerance even more.
Update IPMetric API and document it.
Update FastMKS API and do some documentation. Add some new constructors for
Remove base option -- just for now -- and update calls to FastMKS constructor
Clean up rules file a little bit; make BaseCase forced inline.
Remove parameters that don't exist.
Stop counting kernel evaluations and distance evaluations. This may be brought
Modify main executable to support --base option again, and give better
Don't use global distanceEvaluations anymore. Remove debugging output.
So Doxygen picks up that comment too...
Clean up polynomial kernel and reverse input arguments so they are now in line
Update for PolynomialKernel constructor API change.
I don't have a reliable connection, so check this in so I can work on it from my
Fix reference.
Fix reference.
Finished FastMKS tutorial.
Add new tutorial to list.
Fix @file lines.
Fix @file lines.
Add links to new tutorials.
A notice that FastCluster() doesn't work.
Update documentation (#275).
Patch for #278, contributed by Marcus Edel (thanks!).
Avoid inverting empty matrices. Also fix a possible uninitialized memory issue.
Merge in history for 1.0.5.
Two functions which are useful for RangeSearch.
Add RangeDistance() hooks to HRectBound.
Incompetence is a surprisingly accurate predictor of build-breaking checkins.
Incremental checkin so I can work from another system. Begins outline of the
Add NumDescendants() and Descendant() functions which will make things much
Test NumDescendants() and Descendant() instead of Begin() and Count() (since
Add Descendant() and NumDescendants() functions.
Test the Descendant() and NumDescendants() functions. These tests were
Fix warning.
Add HasSelfChildren trait.
Tests for HasSelfChildren trait.
Revamp RangeSearch as per #244. Now this works with cover trees too!
Comprehensive test for range search with cover trees.
Grevious spelling mistake.
A commit from a long time ago shows I committed the Contains() function without
Finally add test for Range::Contains(Range).
I'm not sure what the older test was, but it was undocumented, so I removed it,
Fix #280 and revamp KernelPCA implementation. It should now be much faster.
Add new contributor.
Update copyright.
Minor formatting fixes and better documentation.
Stupid const error. Did I not test it?
Move IPMetric to general metrics directory since it will be useful for other
Use Log::Assert.
Move IPMetric to mlpack::metric not mlpack::fastmks.
Document what the namespace contains.
Fix for #289 (thanks Marcus)
Remove unused file extensions from Doxyfile.
Do not compile DET code on Windows because it causes the compiler to segfault.
Yeah, well, it's not like anything was going to fix the Windows build anyway.
Sometimes the map is empty, and dereferencing an empty iterator results in
Make the NMF decomposition more accurate in a bid to fix the failing test.
Fix unused variable warnings.
Widen tolerances on GMM tests.
Extra cleanup of Windows' ridiculous #define min and #define max. Seriously
Remove unnecessary include.
Remove unnecessary include.
How did that happen?
Reorder includes.
Windows does not like the #define private public hack, so do not use it there.
logNegError is private, so don't test that on Windows.
Copy HISTORY from branches for mlpack 1.0.6 update.
Fix #291, which is a corner case in situations where the dataset consists
Some formatting fixes, and create a new test that tests the scaling to unit
Fix the scaling parameter; what was being done before did not make sense.
Oops, I forgot to remove the random seed from the test...
Make CLI::GetParam<bool> return the same value as CLI::HasParam().
Test that HasParam() returns the same as CLI::GetParam<bool>().
Clarify comments and fix bug that occurs when no query set is specified.
Fix dangling spaces and use Log::Assert() not assert().
Test single-dataset mode. In writing this test, bug #293 was created.
Testing diff in commit emails.
Test diffs in commit emails again.
Move constructor to top of file, and check the size of the s and y cubes before
Rename a few tests so they compile correctly.
So, actually compiling the L-BFGS test might be a good thing...
Comment out --fast_kmeans option so it does not work at all, for now.
I have been looking for this memory leak for months. Apparently I forgot that
Does this fix the cover tree two datasets test? It seems to on this box.
Don't recurse into the map pruning section if the map is already empty.
Add utility functions to normalize labels.
Modify core.hpp to include label normalization methods and update build
Test label normalization.
Remove debugging output.
This may fix the segfaulting in the cover tree tests.
Change label type to arma::Col<size_t> not arma::uvec.
Change label type to arma::Col<size_t> not arma::uvec (this is more in line with
Update NaiveBayesClassifier API to take labels as a separate vector. Also,
Uncomment checks that weren't failing in the NBC test and update for newer
Use arma::Col<size_t> instead of arma::uvec for labels.
Normalize the labels before performing computation, and use arma::Col<size_t>
Update test to use arma::Col<size_t> for labels instead of arma::uvec.
This should fix the failing build on old Armadillo versions.
Oh holy crap, I am the worst, and I have broken everything.
I always say "build before you check in!" and then the simple fix I try to
Older versions of Armadillo require as_scalar() because gcc isn't able to figure
Simplify centering code. Maybe it's faster?
Clean up PCA test.
Refactor PCA to use SVD because it is faster.
Minor formatting fixes, make things const 'cause that's what's cool to do, issue
Spelling fix.
Remove c_str() where possible.
Remove c_str() where possible.
Widen tolerance on HMM test.
Fix misleading comment.
Marcus, finder of errors, has found yet another one.
Adjust tolerances.
Adjust tolerances.
Minor version update. This is not a very maintainable solution...
For now, don't build the CF package. It uses sp_mat and that isn't included in
Clean up trailing whitespace, reformat a few lines.
Code cleanup, and refactor DTBRules so it does not depend on
Add a parenthesis to fix some grammer. A big deal!
Clean up RANN code, document tau parameter more thoroughly, and refactor
Add --cover_tree option to range_search.
When removing implicit nodes, ParentDistance() was not being correctly
Add some changes from Sumedh (#298). This improves the Predict() function and
Add new contributor.
Fix compatibility with older Armadillo versions and fix warning in
Handle corner case where ||a|| or ||b|| is equal to 0 (and prevent division by
Fix a comment.
Fix output, because it does not output the squared distance any more.
Update documentation for new output; squared length is not given.
Add some new functions from Sumedh.
Add test functions for new stuff from Sumedh.
Add -V option to specify how much variance to retain.
Add lastKernel and lastKernelNode for pre-emptive child pruning.
Add KernelTraits, a useful template class that can tell you about things, like
Just include all the kernels, because I mean, why not?
Add a test for the KernelTraits class, and a long rant which explains why this
No need to transpose matrices.
This was the version of code used for the FastMKS benchmarks in the recently
Print base cases and scores as output even when not debugging.
Often number of prunes can be useful information, to make sure that anything at
Uh, this should fix the broken build. I will clean this up in the forthcoming
Add functions to get number of base cases, number of node combinations visited.
Overhaul NeighborSearch so that it only needs one overload of Score() and does
Update test for new NeighborSearchStat class.
Two things: actually do some pruning, and, get parent base case evaluations
Add RangeSearchStat class.
Move to right namespace.
Use RangeSearchStat (although nothing is being done with it yet).
Use RangeSearchStat in cover tree objects.
So, to test this file, you have to type 'make range_search'...
Refactor test to clean tree statistics before running new range searches.
Refactor RangeSearch to work properly for both cover trees and kd-trees with the
Fix comment.
Use RangeSearchStat with cover trees.
r15817 overwrote the current tree tests with ones from mlpack 1.0.4. This
For now, don't build the CF test. This is because CF depends on sp_mat, which
Remove EuclideanDistance() and CosineSimilarity() functions; instead, use
Fix compilation errors and merge actual changes from r15826.
The parent-child pruning bounds were too tight. They did not consider one of
Update tutorial.
A few fixes.
A few more fixes.
Hey look, I removed three lines of code while not changing the functionality of
Integrate ComputeCost() as ComputeError() for #298, written by Sumedh.
Add test for ComputeError() for #298.
Use Sumedh's dataset for the perfect fit test.
Interesting that this compiles even though the sum of a dot product is a
Fix warning, add const.
Make Predict() function const-correct.
Widen tolerances.
Very minor syntax fixes.
Add lambda parameter, so this now supports ridge regression.
Use an empty dataset, like Sumedh suggested, to test ridge regression.
Avoid an additional matrix copy (insert_rows() and shed_rows() are a copy each
Fix other constructors so they play okay with lambda.
Minor typo.
Fix in implementation to avoid copies.
Add --lambda option to linear_regression.
Update documentation.
Add section on ridge regression.
Add a note about running a timer multiple times.
Update NMF to work with sparse matrices also.
More fixes for correct sparse NMF.
Test sparse NMF.
Armadillo 3.6.0 will be required for 1.0.7 because that is the first version
Update documentation to reflect Armadillo 3.6.0 requirement.
Update documentation to reflect 3.6.0 requirement.
Because we now require Armadillo 3.6.0, we can use each_row() and each_col()
Fix comment headers for doxygen, remove trailing spaces, and use NMF instead of
Instead of using ALS, use NMF with a sparse matrix.
Remove als directory.
Reformat GetRecommendations() function and rearrange cf.cpp to reflect ordering
Why not call CleanData() in the constructor instead of repeatedly in other parts
Clean up CleanData() function. Don't use temporary matrices; there's no point
Minor comment fix.
Use sparse matrix batch constructor.
Clean up Decompose().
Decompose() is only called once, so just inline it because it's simple.
Remove GenerateRating() function because it's only one line and only used in one
Remove CalculateApproximateRatings() since it is only ever called once.
Clean up Query(). It makes me feel a little gross to be so pedantic as to
Inline CreateQuery() function since it is only used once, and use better
Remove GetNeighbourhood() because it is only called once. The check that
Remove CalculateAverages() since it is only called once, and inline it into
Refactor CalculateTopRecommendations(), including a complete overhaul of how
Issue a warning if the correct number of recommendations could not be provided.
Remove CalculateTopRecommendations() function, because it was only called once.
The very large and dense 'mask' matrix is now unnecessary.
No! The spaces were WRONG!
Remove Query() function as it is only used once; inline it into
Remove method that allows modifying the data matrix, because references can't be
Clean up CFTest, and fix some comments that were wrong.
Add convenient function to get sparse matrix.
Add a ridge regression test case (huh, I wonder how I forgot to check this in
Add a test to make sure the output of the CF object is reasonable. I think this
Clean up main executable; a bit of const-correctness pedantry, and don't use
Fix comment (thanks Marcus).
Build the CF test.
Build CF module.
When --query_file is specified, only give recommendations for those users.
Remove options for output files that weren't being used, and comment out options
Better comments for unimplemented functionality.
Actually use number of recommendations and size of neighborhood in calculations.
More comprehensive documentation on options and input/output formats.
Refactor EMFit<> so that the covariance constraint is a template parameter, and
Make function static.
Add tests for NoConstraint and PositiveDefiniteCovariance.
Rename PositiveDefiniteCovariance to PositiveDefiniteConstraint, because I think
Update name of constraint class.
Oh hey, I have to check this in too.
Add DiagonalConstraint.
Add test for DiagonalConstraint.
Add EigenvalueRatioConstraint class for EMFit.
Add test for EigenvalueRatioConstraint.
What, how did I miss this? I definitely built the test and checked it...
Remove fake functions that should only be specific to the kd-tree.
This is premature; wait for this until later.
If the root node ends up having an implicit child (not an illicit child!),
Remove unnecessary functions that were originally for kd-tree compatibility.
Handle cases where the reference map is empty a little better.
Overhaul RASearchRules so that they will work correctly with cover trees.
Test RANN with cover trees.
Add a note that this does not work.
Do not compile MVU.
Fix some comments. No functionality change, and also this was probably
Yeah, it makes a difference to inline the BaseCase function (#281).
Force inlining (#281).
Backport batch insertion constructor to Armadillo < 3.810.0.
Remove backporting for versions earlier than 3.6.0 because that's just not
Oh, right, update the least maintainable part of the entire build system that I
Update copyright file to include new contributors.
Update citation.
Update changelogs.
Minor updates for normalized kernels.
One more thing...
Update to latest version number.
Widen tolerances slightly.
Move DTBStat into a separate file.
Add Epanechnikov kernel for kernel PCA.
Allow GMMs to be trained using the existing model as a starting point. This
Add tests for estimation with the existing model as the initial point.
Add logistic regression directory.
Initial commit of logistic regression by Sumedh Ghaisas (#305).
Add some comments and fix a little bit of formatting.
Rename LogisticRegressionFunction to LogisticFunction.
LogisticFunction is incorrect; it's actually the objective function for logistic
Refactor Evaluate() function so that it works alright, and eliminate unnecessary
Add test for LogisticRegressionFunction::Evaluate().
Oh yeah, this is necessary...
Add a randomized test for the logistic regression likelihood function that is
Add test for regularization of objective function.
Add test for Gradient().
Add correct implementation of Gradient() function.
Make Gradient() const and add comments.
Add some comments.
Remove getSigmoid() and add class documentation.
Break Predict() instead of the whole build.
Revamp Evaluate(parameters, i) for SGD and related optimizers. NumFunctions()
Add test for Evaluate(parameters, i) for SGD and related optimizers.
Test regularization for separable Evaluate().
Update Gradient() for the separable case.
Test Gradient() in the separable case.
No need to multiply by responses[i] or (1 - responses[i]) because those
Add test for regularization in Gradient().
Add a test for the separable Gradient() function.
And this is why I hate maintaining documentation for things that I don't
Remove memory leak (#310). Thanks to bianjiang for pointing this out.
Don't print "Iteration X of 0."; just "Iteration X".
Refactor functions so that they do not expect the extra column of ones for the
Refactor tests so that they do not give the extra column of ones for the
Make predictors and responses const.
Make predictors and responses const.
Don't hold lambda in LogisticRegression because it isn't necessary. Also make
Refactor LogisticRegression class. LearnModel() can be private, and we can
Add tests for actual LogisticRegression object.
Goodbye, slightly misleading documentation.
Add function to get the function that is being optimized.
Add function to get predictors and responses.
Add a constructor that allows passing an instantiated optimizer.
Test constructor that takes an instantiated optimizer.
Update history file incrementally, because doing this all at once at release
Add FurthestPointDistance() function.
Test BinarySpaceTree::FurthestPointDistance().
Implement FurthestPointDistance() for cover trees.
Regularization gets subtracted, not added. Thanks to Sumedh for pointing this
Update test for positive regularization... oops...
Clarify comment.
Remove predictors and responses because they don't need to be stored by the
Don't hold the optimizer and error function since they are only needed at
Add main executable for logistic regression.
I don't remember doing this, and I have no idea when it was, but hey, using
Add information so a version can be obtained easily during runtime and also at
Some documentation on versioning information.
Oops, a typo.
Link to tutorial on versioning information in core.hpp.
Update so that it gets compiled into libmlpack.so.
CMake script to create svnversion.hpp, if needed.
CMake scripts to find and update svnversion.hpp, if necessary.
Fix dependency on stringstream.
Safe check for if we are in an svn repo.
Remove redundant check for working copy.
Add svnversion.hpp to list of sources to track, if necessary.
Fix error so that core.hpp is properly included.
Ignore svnversion.hpp.
Update copyright for the new year.
Add Mudit's name to the list of contributors.
Increase precision of saves.
When using the constructors that don't specify a model, make sure we create an
svn:ignore --> 'build*' in case you have multiple build directories.
This wasn't actually calculating the variance correctly.
Handle cases where scales are 0 correctly.
Pull in updated history from version 1.0.8.
Ticket #314 resulted in a bunch of useful changes.
Fix from Michael Fox for #242.
Add tests when the data matrix has linearly dependent features.
Add new contributor.
Fix spacing.
Add CMake configuration for LRSDP, and split it properly into cpp/hpp/_impl.hpp
Don't make an extra line when indenting things.
convert << util::Indent(probabilities);
Add new contributor.
Update ToString() for all kernels except the PSpectrumStringKernel.
Update so filename is like other filenames.
Remove license, that doesn't get applied until a release (until then it's
Inline non-templated constructor.
Update documentation (thanks Yubao).
Fix documentation (#321); from Siddharth.
Fix collaborative filtering test (#323).
Add a boolean specifying whether or not the dataset is rearranged when the tree
Cache the distance from the center of the node to the center of the parent node.
Test BinarySpaceTree<...>::ParentDistance().
Also test ParentDistance() in the case where the tree is built and mappings are
TraversalInfo, a new idea for doing things. This will need to be further
TraversalInfo class used by nearest-neighbor-like problems. Maybe it could be
Change build to include ns_traversal_info.hpp.
Add traversal_info.hpp to build system although I don't think it's used
Make rules classes for various dual-tree algorithms support (but not use) the
Minor changes to SortDistance().
Overhaul NeighborSearchRules to work correctly with TraversalInfo objects. This
Modify SortDistance() usage because SortDistance() API has changed slightly.
Modify BinarySpaceTree::DualTreeTraverser to properly handle TraversalInfo
Modify CoverTree::DualTreeTraverser to properly handle TraversalInfo objects.
Adapt SortPolicyTest for new API.
Remove unused score variable; this fixes a lot of warnings.
Patch from Siddharth for #324.
Remove license text.
Slight code formatting modifications.
Don't initialize empty distributions.
Remove unnecessary newlines from after mean and covariance output.
Actually print the kernel.
Minor fixes to ToString().
Minor fixes to ToString().
Minor changes to ToString().
Minor changes to ToString().
Minor fixes to AugLagrangian ToString() methods.
Move things around so LRSDP can actually be included in stuff.
Some updates to what has been going on (lots of things!).
Ah, right, one more thing.
Minor changes to ToString() output.
Minor changes to tests; in some cases matrices/vectors are now initialized so
Remove PeriodicHRectBound (#30).
Remove this file too...
Remove PeriodicHRectBound from tree tests.
Denote that we removed PeriodicHRectBound.
PeriodicHRectBound is removed (#30).
Revert commit by unknown contributor.
Test commit
Revert test commit.
Update citation format.
Fix from Siddharth, fixes #324.
Add new contributor.
Fix formatting and fix contributor information.
Didn't mean to check in arma_traits.hpp...
Oops, forgot to check in this change from Siddharth.
Example tree. Not really to be used, but for documentation.
Refactoring from Saheb: don't do naive search with trees.
Add new contributor.
Clean up RangeSearch implementation so it works with TraversalInfo struct.
Use TraversalInfo for FastMKS. Right now, the parent-child prune is not
When the parent-child rule can't be applied, the correct bound wasn't being used
Do child-parent and parent-parent prunes correctly for FastMKS. This actually
Update the line about dual-tree algorithms being faster. 'cause they are.
The Prescore() and PrescoreQ() functions aren't used anymore because I figured
Patch from Saheb: do actual naive search for RangeSearch and NeighborSearch
Add some Armadillo traits for template metaprogramming. This abstraction may
By default, include arma_traits.hpp.
Refactor MinDistance(), MaxDistance(), and RangeDistance() to accept any
Refactor MinDistance(), MaxDistance(), and RangeDistance() to accept arbitrary
Having an implementation for the example tree is kind of a dumb idea. Also make
Clean up some namespacing, and add a test for sparse AllkNN using kd-trees.
Templatize arguments for BestPointToNodeDistance().
Refactor NeighborSearch so it works with arbitrary TreeType::Mat types. That
No more implementation.
Stop timers correctly when Log::Fatal is called (or when Load() or Save() return
Rank is not yet a parameter, but this heuristic from Siddharth improves upon the
Fix mixup of rows and columns.
Widen tolerances ... again.
Patch from Siddharth: make the rank parameterizable, and merge the constructors
Update for changed CF API (patch from Siddharth).
Some changes to LaTeX options in the Doxyfile.
Explicitly use namespace mlpack::neighbor.
Remove using directive that has been there for six years. Sigh...
Remove numPrunes -- it isn't used.
The maxLeafSize parameter is unused (other than an assert) so remove it
Initialize uninitialized variable (#336).
Remove numberOfPrunes variable, and initialize baseCase (#336).
Patch from Siddharth: templatize CF to accept arbitrary types of factorizers.
Fix regression in r16308, which slowed down cover tree traversals by potentially
Actually use the right parameter name.
Ok, handle NaNs correctly, and also check this in in trunk, not in the tags...
Remove incorrect comments.
Better rule, which forces the score to 0 for AllkNN. Not sure if it'll work for AllkFN. Also, I think there may be a bug in the traversal info handling for the BinarySpaceTree DualTreeTraverser.
What was I thinking? This is a _far_ better solution than r16359.
Modified patch from Saheb for #301; this unifies the constructors for
Fix to go with patch from Saheb... forgot to check this in earlier.
Make the ExhaustiveSyntheticTest use kd-trees with a leafSize of 1. This
Oops, use single-tree for the second iteration.
Through the magic of regular expressions, I've refactored this test to use
Update documentation to reflect changes in RangeSearch.
Add new contributor.
Make parameter const because const-correctness is a good thing.
Don't use the SquaredEuclideanDistance.
Don't use the squared Euclidean distance.
Fix minor error that I didn't correct last time.
Refactor LRSDP into the main class and a separate function (LRSDPFunction).
Better ToString() output.
Annotate changes to LRSDP.
Add new contributor.
Whatever bug used to be here before isn't here now.
Use const reference parameter so it works with temporaries too.
Doxygen fix so that local paths aren't included in the built documentation.
Actually catch all of the instances where single quotes start lines.
Patch from Siddharth for #342.
Document API change in an attempt to piss people off less when their programs
Clean up implementation of GetRecommendations().
Update documentation due to API change.
Spelling fix; thanks Barak!
Patch from Saheb for #301; refactor RangeSearch constructors so that leafSize is
Modify test for new RangeSearch API.
Add rank parameter. This might not be applicable to when we have other
Minor documentation fix, and sometimes the labels need to be transposed.
Don't transpose the labels upon loading; expect that they are going to be one
Get the number of classes correctly.
Don't transpose on save; one point per line.
Overhaul implementation; do not use gmm::phi(). This gives serious speedup, as
Adapted patch from Vahab for #344: incremental algorithm for variance
Test incremental variance functionality.
Change to two-pass algorithm suggested by Vahab in #344.
Add new contributor.
Add sparse autoencoder contribution by Siddharth. This is the version given in
Add test for sparse autoencoder, contributed by Siddharth.
First pass: add file headers, include guards, and then my vimrc auto-stripped
Minor (and ultimately trivial) documentation changes; add documentation for
Syntax cleanup; just some spacing. No functionality change.
Adapt test to work in the larger framework of mlpack tests.
Simple style changes; no functionality change.
CMake configuration to compile sparse autoencoders.
Build sparse autoencoder as part of mlpack.
Test sparse autoencoder.
Remove unused variables to fix warnings.
Change Sigmoid() function to avoid matrix copies via the return value.
A better fix for the failing build.
Revert accidental commit.
Rewrite NMFALSTest so that random failures should be less likely.
Const parameters will cause this to be two billion times faster.
Fix comment and clarify that it's pertaining to the runtime constructor, not the
It turns out the implementation of FurthestPointDistance() was just wrong.
The test for FurthestPointDistance() was wrong also.
Add new contributor.
Remove the Pelleg-Moore k-means implementation; it is being replaced.
Remove HasParentDistance trait, becase it wasn't used anywhere.
Don't select points from clusters of size 1.
Ensure that BaseCase() is called right after a node is scored.
It's no longer reasonable to say the FASTLab developed mlpack, because first,
What was this macro even for?
Refactor core.hpp into two files; one for non-mlpack includes, and one for everything else.
Use prereqs.hpp to avoid weird include order dependency issues.
Use prereqs.hpp instead of core.hpp; core.hpp is required for the implementation, though.
Include stdint, for uint32_t support.
Use prereqs.hpp instead of core.hpp; however, the implementation requires core.hpp.
Fix header guard names. This is an incredibly pedantic fix.
Remove unnecessary includes.
Trivial spelling fix.
Typo which causes a segfault.
Oops, this actually happens in two places.
Inline the simple R tree descent heuristic.
Remove leafSize parameter from DTB constructor.
Fix #334 by ensuring vector accesses don't go out of bounds.
Link against libstd++ when using Clang, and also use -Wall.
Fix for convergence, because sometimes the residue may increase (especially with
Make a note that this set of update rules often creates lots of NaNs when sparse
Significant refactoring of NMF tests. The sparse tests were generally invalid
Remove backup file from emacs or some other inferior editor that isn't vim.
First pass: comment standardization, fix header guard names, move .cpp to .hpp
Use bool instead of int.
Minor changes to test. const-correctness and comment normalization for Doxygen.
Use const double where possible instead of having a variable used throughout the
For clarity, use separate split and binLabels objects instead of storing the label in the split matrix. No casting is necessary anymore.
Remove unused variables.
Oops, missed one unused variable.
Remove classLabels; it isn't necessary for the DecisionStump class to hold it.
Easy fix for #355.
Document minor fix.
Remove oneClass and defaultClass variables. There is a shortcut that can be taken when all the labels are the same, but the Entropy() function does not appear to be working correctly.
Very simple change to fix build on i386.
Initial commit of simulated annealing optimizer from Zhihao Lou.
Minor refactoring for brevity.
Move LaplaceDistribution to mlpack::distribution and expand upon it, but then
Create separate target for moving mlpack headers. This should fix #322.
Remove now-unnecessary include.
Remove documentation for MoveDistributionType.
Rearrange parameters -- maxIterations is probably the most likely to be changed, and also maxIterations tends to be the first parameter for other algorithms.
Rename parameters, clean up documentation; very minor tweaks. No functionality changes.
Refactor to avoid holding variables in the class itself (reduces the size of SA a bit). Remove an unnecessary variable too. Minor changes, no public API changes.
Add comments to private functions in header file.
Explicitly use arma::sign().
arma::sign() doesn't exist in Armadillo pre-3.920.
Why was svn:ignore set for cf.cpp? Removed.
svn:ignore build directories.
Minor cleanups; no functionality changes. Make some things const where
Set default CoolingSchedule.
Add some more tests for simulated annealing, including a highly nonconvex
Refactor tree construction so that arbitrary tree types can be constructed.
Refactor tests, use BOOST_REQUIRE_EQUAL(), and add a test for EMST using cover
Oops, I did not mean to comment out the sparse k-means test.
Bump minimum required Boost version to 1.49 for boost.heap.
Split RAQueryStat into its own class.
Refactor RASearch so that it does not accept a leafSize parameter and can build
Fix constructor calls, and automatically construct a cover tree with the default
First pass -- move files to match naming policy, change initialize() to
Minor formatting changes according to the style guide (mostly, I think?).
Minor refactoring of AMF class; mostly renaming for consistency and
Trivial spacing fixes.
Rename for slightly changed API.
Move warning to prereqs.hpp, because sometimes prereqs.hpp is included and
Don't include <armadillo> explicitly, because <mlpack/core.hpp> does that
Add new contributor.
Note that we now have simulated annealing.
Don't include <armadillo> before <mlpack/core.hpp>.
Disambiguate: math::RandomSeed() -> mlpack::math::RandomSeed(). Issue noted by
Patch from Zhihao: sa_update.diff.
Return the correct type of the matrix, because it isn't necessarily dense.
clang complains when default parameters aren't part of the original declaration.
Add support for HMM initial states. Slight modification of API for creating
Test HMM initial probabilities.
Document that #315 is fixed.
Fix some formatting, fix backwards entropy splitting, add getters/setters, and
Another test to make sure the correct splitting attribute is used.
Include mlpack/core.hpp.
Const-correctness and 80-character lines... very trivial fix, no functionality
Fix some formatting issues; no functionality change.
Use bool instead of int for tracking convergence.
Don't use arma::unique() because it's slow.
Very minor changes.
Lengthen comments that weren't 80 columns long. This may be the most trivial
Add MinimumBoundDistance().
Fix elusive bug that only occurred in particularly rare situations.
Add MinWidth(), which is a better solution than having the tree calculate it by
Test MinWidth().
Use the bound's cached MinWidth() for MinimumBoundDistance().
Use slightly safer Width().
Oops, this needed to be divided by 2.
Simple style changes for consistency.
Rename executable.
Refactor main executable. Some further refactorization will need to be done
Rename executable.
The size parameter is unused outside the constructor; also, commit this change
Actually calculate score and base case for first node combination.
Comment normalization.
Refactor to be stricter with types (arma::Col<size_t> instead of arma::vec).
Point out that there is a known bug.
Some notes on some things I've done.
Additional things that have changed. I incorrectly wrote in the last commit
Ball tree tests for EMST.
Initialize reverseStepCount to 0 to avoid memory issues.
Fix an uninitialized value.
Increase tolerances a little bit, because they were failing in some cases.
For each random dataset, ensure that the size of the implied user/item matrix is
Patch from Sumedh: fix some uninitialized values.
Patch from sumedh: Mat::row_col_iterator
Patch from Sumedh: more tests for SVD
Patch from Sumedh: tests for row_col_iterator
Propagate HISTORY.txt change to trunk.
Update documentation.
Propagate documentation fixes to trunk.
Merge in changes from release branch. I guess I should have done all this
Fix warnings.
This warning only appears on i386.
Fix botched LaTeX formula.
Set date of release.
More comprehensive tests.
Fix typo.
Don't do base cases before recursing. This is slightly cleaner code and will
Extremely minor changes.
Refactor KMeans so that the actual Lloyd iteration step is separate, since there
Add some comments.
Refactor test for changed API.
Further refactoring of KMeans. Fix MaxVarianceNewCluster, and also change it so
Fix changed API.
Explicit cast for older versions of Armadillo.
Explicit cast to arma::vec for old versions of Armadillo.
Yet another reverse-compatibility fix for Armadillo.
Return statements for operator++() and operator--().
Fix out-of-order initialization warnings.
Fix error in random sample generation.
Add LaplaceDistribution to the list of default-ly included distributions.
Minor code cleanups.
Remove duplicate declaration of ReadFile() to fix the failing build.
Remove const identifier since it gets ignored and throws a warning.
Minor formatting changes for row_col_iterators, mostly to adhere to the
Test sparse iterators, when we can.
Fix incorrect check (how did this happen?).
Oops, I fixed this backwards. The actual error is the output.
Add header comments and clean up BiBTeX citation a bit.
Add header comments, fix header guard naming to be in line with the rest of the
Add some const and fix some formatting.
Change names of functions.
Some formatting fixes.
Simplify a matrix calculation.
Set ARMA_USE_U64S64 in hopes that the types of problems Gilles is having on the
Return *this for operator--().
Fix odd tabbing issue.
First pass: make lines 80 characters long, tabs to spaces, and bracket surgery
Typing failure.
Don't add row_col_iterator support after 4.349 (currently svn trunk) since
When Conrad took the patch, he stripped out a lot of compatibility between
First pass: make things 80 characters, minor style fixes.
How did I accidentally remove two lines? I'm not actually sure.
Minor formatting change, and use zeros() instead of fill().
First pass: try to make things 80 characters (I didn't touch the big long type
Typedef to the rescue! Much easier to read now.
Simplify some loops.
Significant test refactoring for style. Also, use BOOST_REQUIRE_CLOSE and
Use templates to significantly simplify code and remove multiple versions of the
First pass: make it 80 characters, fix a few coding conventions. No real
First pass: line length, bracket surgery (similar to rocket surgery).
First pass on R* tree split code; make things 80 columns, use convenience
Some brackets and stuff like that.
Only depend on automatic linking when MSVC is used, and prep for OpenMP support.
Add HRectBound<>::Volume() and a test for it.
Clarify some difficult ternary operator operations (the compiler should give
Revert most of r17065, since my testing was actually on the R* tree and not on
Inline HRectBound functions. Minor to negligible speedup, but certainly no
arma::prod is faster, in this case.
Avoid math::Range copy, although realistically gcc should be avoiding that
Simplify methods a little, and use int& instead of int*.
Don't use auxiliary structures; find the best node with O(1) storage. Minor
Formatting fixes for GMM conversion utility.
Remove trailing spaces thanks to vimrc, and fix comment correctness.
Spacing issues and remove apparent debug output.
Standardization of comments for doxygen.
Comment normalization for doxygen, and remove no-longer-relevant comment.
Convert tabs to spaces.
Convert tabs to spaces.
Resurrect Phi tests from gmm_test.cpp.
I forgot to add Udit to the list of contributors!
A first draft of a smarter FindArmadillo script, which takes into account
Be quiet when finding things so as to not duplicate output.
Use FATAL_ERROR instead of FATAL. Also find ARPACK quietly.
Display base cases and scores for single-tree mode.
Refactor CalculateBound() and improve to fix regressions noted in #365. This
Correctly handle SortPolicy abstraction.
Workaround for the fact that BallBounds may have larger furthest descendant
Minor formatting changes.
Forward-port fix for usage of log2().
Note that the Armadillo code is MPL-licensed.
Backport another sparse matrix constructor for softmax regression.
Update HISTORY.txt.
Switch int to size_t in order to fix a very large number of warnings.
Fix some more signed/unsigned comparison warnings that I introduced with the
Fix even more warnings that I've introduced.
I fixed a little bit, but I know this doesn't fix everything.
Comment out XTreeTraverser test for now as per #368.
Add comment pointing out that there is a bug.
Move MAX_OVERLAP to be a member in the mlpack::tree namespace to fix errors on
Add explicit declarations of template function specializations for linker fixes
Tabs to spaces.
Spacing and line length fixes.
Fix a couple bugs pointed out by Francois Berrier: SGD isn't actually shuffling,
Refactor k-means significantly. Remove overclustering since I think nobody is
Implement Elkan's algorithm for k-means (it's pretty fast).
Remove comment about overclustering.
Remove references to overclustering from tutorial.
Refactor test to remove overclustering parameter.
Update and clarify build tutorial, since DEBUG and PROFILE are OFF by default in
Refactor for different KMeans API.
Refactor for API change... forgot to check this one in.
Add a warning if the user wants 0 clusters, because the thing is probably going
Explicit std::sqrt() call.
Add implementation of Hamerly's algorithm.
Refactor input arguments so --algorithm is an accepted parameter, which provides
Refactor ElkanTest and add a test for Hamerly's algorithm.
Fix distance calculations, and fix residual calculation.
Fix a bug; now this algorithm is much faster.
Add Pelleg-Moore k-means. This implementation is faster and prunes more tightly
Add test for Pelleg-Moore k-means clustering.
Refactor: only track distanceCalculations, not scores and baseCases. Also
Clean up an unnecessary sort, and remove spareBlacklist.
Comment the Rules class a little better.
Better comments for the PellegMooreKMeans class.
I suppose we should exercise at least some caution in the destructor.
Don't ignore distance calculations during cluster-moving calculations.
Force C++11 support for future versions of mlpack. I wouldn't be surprised if
Allow std::cout << mlpackObject, as per #319.
Test std::ostream << mlpackObject.
Now we have C++11, but there's no constructor copypasta problem anymore.
Oops, include ostream_extra.hpp.
A prototype algorithm for k-means clustering, which probably works best when k
A test for the DTNN k-means algorithm.
Safer includes, for the situation where the user does something not smart.
Yet another instance of me failing to commit all my changes. Add a BaseCases()
Fix a bug that meant that centroidsOther was copied only when it shouldn't have
Properly handle the case where the tree doesn't rearrange points -- like the
Add test for CoverTreeDTNNKMeans.
Make the Mahalanobis distance a true metric by default.
Fix -Wreorder warnings after reordering of data members in class declaration.
Minor formatting changes and streamlining of Armadillo expressions.
Minor formatting fixes: tabs->spaces, etc.
Minor spacing fix.
The const gets ignored (-Wignored-qualifiers).
Fix use of uninitialized value; this should help segfaulting SVDBatch tests.
Increase number of samples and give debugging output, in order to try and track
Fix logistic regression tests by enforcing a tighter tolerance for SGD
This is an experimental method that I am working on. Right now it is not very
Add DualTreeKMeans files to CMakeLists.txt.
Add DualTreeKMeans as an option to the kmeans program (and also DTNN with cover
Add a simple test for DualTreeKMeans.
Be explicit with calls to arma:: functions. Although gcc accepts this as-is, we
Add a semi-hackish breadth-first traverser. The tree abstractions will need to
Add breadth first traverser.
Here's the file I forgot -- include the BreadthFirstDualTreeTraverser class
Use FATAL_ERROR instead of FATAL, so that CMake will actually crash when C++11
Refactor code for better comments and better adherence to coding conventions.
Fix incorrect class name.
Refactor Elkan-type prune into its own method, for simplicity.
Add Pelleg-Moore type prune. This improves performance -- at least a bit.
Loosen tolerance until a better solution is devised (currently I am waiting on
Remove debugging random seed.
strlen() returns the length of the string but you must account for the null
If gradient2 or gradient1 are zero, then BOOST_REQUIRE_CLOSE will fail, so use
Not sure how I missed this spelling error...
Smarter handling of HDF5 dependency search, especially for Debian systems where
The calculation here was actually incorrect.
Refactor CountMostFreq() so it is faster, simpler, and doesn't sometimes return
Better handling of the weird case when includes are needed but the library isn't.
Slightly loosen tolerances for NMF tests.
Fix -Wunintialized, reported by govg.
Pedanticism: return a value at the end of main().
Nope, turns out I am wrong. C++03, C++11, and C++14 all assume a program
Fix uninitialized memory issue (dsPredictions was never set).
Don't test on Armadillo 4.300.0 through 4.400.x because there is a bug in
Issue a runtime error if the user is using Armadillo 4.300.x through 4.400.x and
Refactor GeneralizedRosenbrockTest to deal with intermittent failures better.
Refactor for cleaner code and avoid storing WH explicitly if possible.
Minor code cleanups.
Somehow this never got added to the CMakeLists.txt.
Remove debugging output.
Refactor test with negative elements to decompose the random matrix into its
Disable C4519 errors entirely.
Include prereqs.hpp for compiler definitions and adjustments.
Disable C4519 in prereqs.hpp not core.hpp.
Handle setting seed properly for Armadillo RNGs past 3.930.
Significantly shrink size of test dataset because this test was taking 10
Fix memory leak.
Widen tolerance slightly.
Widen tolerance slightly.
Widen tolerances slightly. Maybe this test scheme isn't the best?
Check frobenius norm overall instead of just for one element.
Comment out NoCholeskySingularityTest in accordance with #373.
Reduce noise slightly and increase dataset size, which will slow down the test
Tighten convergence tolerance for RastrigrinFunctionTest, since it doesn't seem
Slightly loosen tolerance.
Better handling of small gradient values.
Minor tolerance widening.
Accidentally checked in unstable code.
Slightly widen tolerance.
Handle negative gradient values correctly.
Fix convergence criterion according to Nishant's suggestion.
Loosen tolerance a bit, since it seems to fail once in a while. It's definitely
Tweak SGD parameters a little bit.
Remove random seed to make test reproducible.
Widen tolerance for norm difference, and tweak parameters a little bit.
Minor style fixes.
Use maxIterations for Newton method loop instead of nested Armijo line search.
Fix memory leak, although I'm not sure it's responsible for the i386 failures.
Adjust tolerances.
The failure probability is already small, but not small enough it seems.
Better handling of Armadillo configuration files, since ARMA_USE_HDF5 may appear
Update with 1.0.11 release notes.
Update notes; more has since been added to the k-means code.
Merge changes to mlpack-1.0.11 tag.
Why did I merge that change in? It broke everything. Revert...
Slight readme update to point to main website.
Merge pull request #5 from ajkl/master
Merge pull request #362 from stephentu/sparselrsdp
Merge pull request #371 from stephentu/master
Merge pull request #372 from stephentu/testcase
Merge pull request #373 from stephentu/testsensing
Change to BSD license from LGPL.
Switch to BSD from LGPL, and update a few things.
Remove extraneous licensing information.
MLPACK -> mlpack.
Update version number as a bit of a workaround.
Fix failed build.
Remove Covariances() and Means(); fixes #346.
Add -lm for failing clang build on some systems.
Comment out parameter name instead of (void)ing it.
Comment out parameter name instead of (void)ing it.
Style fixes (trivial).
Add header guards.
Fix all -Wunused-parameter.
Don't initialize random seed in test.
Fix -Wunused-private-field.
Remove MRKDStatistic; its functionality is gone.
Merge pull request #376 from stephentu/master
Minor style changes.
Merge pull request #374 from stephentu/matrixcompletion
Minor style issues.
Some changes for the sake of Doxygen.
Style fixes: capitalize method names.
Probably needless const-correctness.
Add some backtracing output to CheckValues().
Asleep at the wheel?
Merge pull request #383 from stephentu/pgo
Merge pull request #382 from stephentu/master
Merge pull request #384 from rcurtin/tracedot
Update history with recent changes.
Merge pull request #389 from uditsaxena/master
Fix spacing for include warning.
Minor syntax fixes.
Minor syntax fixes.
Update bug tracker to Github.
Merge pull request #390 from stephentu/master
Properly handle old Armadillo versions.
Merge branch 'ip' of https://github.com/stephentu/mlpack into stephentu-ip
Merge branch 'stephentu-ip'
Refactor to access SDPs through LRSDP::SDP().
Better commenting of the SDP class.
Slight code cleanups for style.
Merge pull request #398 from jaskaran1/master
Refactor notice about LD_LIBRARY_PATH.
Add new contributor.
Merge branch 'master' of https://github.com/jaskaran1/mlpack into jaskaran1-master
Merge branch 'jaskaran1-master'
Fix documentation, thanks to Squalluca.
Revert "older versions of arma do not support unary minus on sparse matrices"
Remove tab character.
Backport operator-(sp_mat) for Armadillo <= 4.000.
Standardize name of test suite.
Fix syntax.
We're not using Java. There's no need for new.
Fix #400 -- remove unneeded specializations.
Fix documentation; thanks to Kumar.
Fix minor misspelling.
Code cleanup; better documentation.
Fix stray forward-slash.
Refactoring.
Fix incorrect variable name.
Refactoring and code cleanup.
Remove unneeded semicolons at end of namespace.
Code cleanup.
Refactor and code cleanup.
Suppress non-bad warnings; they confuse people.
Force high-precision Armadillo saves.
Merge pull request #407 from hritik25/patch-1
Merge pull request #409 from apir8181/issue-344
Non-important spelling and style fixes.
Merge pull request #408 from VladimirGl/Issue#203
Merge pull request #411 from VladimirGl/master
This isn't warning output. Make it "info" instead.
I've concluded that this test isn't useful.
Merge pull request #410 from VladimirGl/randoms
Remove references to Boost.Random.
Armadillo 3.930+ supports inplace_trans() too.
Fix documentation, pointed out by Marcus.
Add new contributors.
Merge pull request #418 from apir8181/issue-332
Add new contributor.
Trivial spelling fix (why am I even bothering?).
Change API slightly to match other code.
Note that softmax regression is done.
Fix commenting before patch application.
Refactor to perform allknn on the clusters. This is done at the start of each iteration. This allows Elkan pruning without an additional distance calculation.
Fix all -Wunused-parameter.
Perform the top-level scoring too.
Some fairly serious refactoring, but it works.
Use ClosestQueryNode() not MaxQueryNodeDistance(). Eventually MaxQueryNodeDistance() will not be reset to DBL_MAX every iteration.
This output is less useful right now.
Don't accidentally take results before finished. We have to wait until all clusters are pruned, not all except one.
Avoid calculating distances after an Elkan prune. Slight, nearly negligible performance gains.
Don't calculate MaxDistance() unless we have to. Fairly significant time savings on this one.
Count the base cases and scores of the kNN run.
Remove unnecessary check; that can never happen.
Try to do an Elkan prune not at a query leaf. It doesn't seem to work right now, though.
Fix warning for unused parameter.
Fix typo, which actually gives a speedup. A fairly trivial speedup, but a speedup nonetheless.
Set FirstBound() after the allknn. Now, checking if FirstBound() == DBL_MAX is unnecessary, although this doesn't (yet) seem to give any additional prunes.
Update FirstBound correctly. Trivial speedup.
Elkan pruning can't prune the best query node. Bugfix. Trivial slowdown.
New stub method for (hopefully) good Elkan prune. This allows us to prune without even needing to recurse.
Oops, bad parameter name.
Rename to Hamerly-type score. Because that's what it is. Although Elkan's algorithm has a type of score that's sort of like this, it's Hamerly's algorithm that only keeps track of the second-closest cluster distance, and that's what we're doing here.
Add second bound.
Fix invalid memory access.
Avoid uninitialized owner field.
A first attempt at a working Hamerly prune. The bounds tighten too much and don't reset, so there's not much speedup, but it's a start.
Add debug output; don't adjust second bound. This provides another minor speedup, but this still is nowhere near as fast as it should be with a properly working Hamerly prune.
Handle SecondClosestBound() a little better. Debugging information is still there, and it is going to need to be seriously refactored. We still don't have properly working Hamerly prunes; they go away after a couple iterations incorrectly.
Be more careful about when to take the last SCB. This gives a trivial speedup, but hey, speedup! Hamerly prunes are still not working properly, but I'm getting there.
Remove unnecessary check for parent's SCB. There actually isn't a need to take the parent's second closest bound preferentially, and it was preventing some valid prunes. This gives a little more (but not enough) Hamerly pruning, and provides (as usual) trivial speedup---but more than none!
Um, I made it faster. We're well into the land of confusion. Confusion will reign until eventual refactoring. Hamerly prunes still don't appear to be working properly after a couple iterations.
Comment out most of the debugging output. It still shows you what's been Hamerly pruned and what hasn't, which is what's important right now.
Count number of points that are Hamerly pruned.
Fix compilation warnings. secondClosest will eventually be removed but is commented for now.
Unset Owner() after failed Hamerly prune. This is better than setting it by hand when we're checking if we can prune.
Remove some debug output we don't need anymore.
Don't set CQN to NULL before recursing. This was an error in TreeUpdate() that caused... some problems that I'm only vaguely aware of as problems. Also refactor one of the second bound rules and comment it so that it makes some semblance of sense.
Fix second bound to not be the first bound. In some situations, MinQueryNodeDistance() was equal to SecondClosestBound(). This fixes that. This also resolves an issue where SecondClosestBound() wasn't properly updated after an Elkan prune.
Last changes for a little while.
I don't think this is worth saving. It also doesn't work very well, but I learned a lot about the bookkeeping I need to do.
Refactor into UpdateOwner(), instead of an ugly loop at the beginning of TreeUpdate().
Remove debug output; implement Pelleg-Moore prune. Now this is faster than the regular dtkm branch. Sometimes starting over is a good thing.
Better speedups, provide more output on prunes.
Add some debugging output. This makes it a bit easier to figure out what is going wrong.
Correct Pelleg-Moore prunes that finish a node. There were cases where a Pelleg-Moore prune would happen before committing the point. This is actually getting pretty fast in terms of base cases, so I am happy with that (for once).
Remove vestigial code. After all, this code isn't generated by genetic algorithms. (Maybe it should be?)
A start at implementing pointwise Hamerly bounds.
Shitty implementation of Elkan-type prune. It makes things faster... a little...
Slightly tighter prune.
Refactor to use new set of rules. How many times will I restart writing this algorithm until I actually get it working well?
Add a StatisticType for DTNN.
Revert back to one point per node.
Refactor UpdateTree() to sometimes Hamerly prune. We aren't properly retaining pruned nodes between iterations, but this is definitely a start and it's basically as fast as any of these attempted algorithms I've written.
More reasonable handling of bound updating. This speeds things up.
Better handling of cover trees.
Run NNS on the centroids. No prune yet.
Apply another prune, but it isn't very effective. Maybe that's an artifact of the datasets I'm currently playing with.
Cache mappings from new to old. Slows it down...? Not sure why there's a slowdown. Doesn't make much sense to me.
Perform prunes on individual points. Significant speedup with respect to number of calculations, no real speedup for runtime. But there is still time to optimize it.
Also use between-cluster-distance prune for points.
No need to reset the bounds when un-pruning. They've been updated correctly all along, even when the node is pruned.
Prune parents when children are pruned.
Refactor: do tree update before kNN search. This will allow us to make tighter prunes.
Recalculate upper bound before giving up on prune. This is done by Hamerly's algorithm and we obtain minor speedup as a result.
Prune a node when all its points are pruned.
Mark parent as pruned if its children are pruned.
Force four-point leaves. This is generally faster than one point. More points are probably even better (to a point... hah) but that requires a large k.
Refactor BaseCase() to apply mappings. This reduces memory usage.
Refactor to re-use distances to clusters. This is better than setting the distances to DBL_MAX every iteration, and provides reasonable speedup.
Use tighter bounds for distances. More speedup. Only increase the distances by the maximum amount those particular clusters could have moved.
Use distances instead of upperBounds. Remove upperBounds entirely. Minor speed improvement (not 100% sure why).
Refactor: remove unnecessary temporary.
Refactoring to reduce runtime of tree update. It speeds things up in terms of distance computations too, a bit.
Refactoring, and tighten a bound for minor speedup.
Coalesce the tree before kNN. Speedup! This is a fairly significant speedup, actually.
Compute max cluster distance after failed prune. This gives us another chance at a prune, and gives very minor speedup.
Make the 'clustering' timer encompass everything. Including the tree building time.
Allow autodetection of number of centroids.
Update reference to Github.
Use existing bounds, if we can.
Try to keep the query and reference levels equal.
Use default leaf size.
Round four. Start over. This time, I proved that the algorithm is right before implementing it. This should help make debugging a lot easier.
Test with regular kd-trees and cover trees. The test conditions for the cover tree need to be adapted a little bit.
Handle cover trees. They don't have two leaves. This still won't work *quite* right for coalescing/decoalescing though.
Refactor DTNNKMeans according to the new algorithm. Lots of stuff torn out. It'll go back in when the time is right.
Make DTNNKMeans work again. Next up, tree coalescion. (Is that a word?)
Do mapping correctly; handle cover trees right.
Refactor to apply mappings earlier.
Basic static pruning. Minor speedup.
Fix a bug. And LastUpperBound() doesn't work. The bugfix speeds thigns up, too.
Add static point prunes. Fairly significant runtime improvement.
Avoid iterating over every point when pruned. Cache the amount the upper bounds and lower bounds must change when the node becomes unpruned.
Coalesce and decoalesce the tree.
Perform tree update at start of iteration. Cache some variables inside DTNNKMeans.
Start applying prune on intercluster distances. Not quite done yet.
Unmap intercluster distances (oops). Minor speedup.
Don't perform cluster 1-NN unless we have to.
Update lower bounds when possible. Surprisingly, no speedup anywhere?
Prune nodes whose points and children are pruned. This gives significant speedup, and on my little test dataset, this is the fastest algorithm yet that I have created.
Implement Rescore(). Minor speedup.
Pre-emptive prunes. Potentially a slowdown. Not always, though, I don't think. I may revert this.
A tighter, but random, prune. Minor speedup. Also add a commented-out check for the lower bounds, and fix a minor bug that screwed them up.
Use one-leaf trees for better performance.
Make the search *actually* breadth-first. Significant speedups result!
More accurate counting of calculations.
Fix a bug where we pruned too tightly. Provide a little more debugging output for errors, too (but this debugging is commented out by default).
Make traversal depth-first in the queries. This results in less memory usage, and some amount of speedup.
Always mark the owner. This fixes some unusual and unexpected floating point errors where the owner will not actually be set.
An attempt at making things faster. Might work?
Revert "An attempt at making things faster. Might work?" It didn't.
Comment out failing tests; to be fixed shortly.
Undef max first (thabks Joseph for pointing this out).
Attempt 2: avoid min/max definitions.
Minor cleanup of backtrace code; all style fixes.
Don't include inside the mlpack namespace.
Link mlpack against backtrace, but not everything.
Include default unconfigured backtrace.hpp file.
Update comments.
Refactor CMake to get version info from git.
Add a comment, and fix macro name.
Refactor tests to eliminate random failures.
Tiny misspelling fix.
Reference Github ticket numbers, not Trac.
Merge pull request #429 from HurricaneTong/latest
Remove trash bloated not-working DualTreeKMeans.
Rename DTNNKMeans to DualTreeKMeans.
Fix uncommitted class name change.
What? What is this file? Why is it here?
Remove tab characters; use spaces.
Preliminary refactoring of RangeSearch.
Update links to Github.
If we are using Armadillo 5+, ARMA_64BIT_WORD is implicit.
Fix warning.
Add Range::Serialize().
Refactor and add Serialize().
Add Serialize() to MahalanobisDistance.
Clarify comments, fix accessors.
Add BallBound<>::Serialize().
Some serialization changes.
Add arma_config.hpp so that it gets installed.
Add Predict() method for predicting individual ratings.
A struct is better here...
Add a tutorial for CF.
Remove unnecessary period.
Fix filename.
Add batch Predict() method.
Remove 'metric' member; we can use it statically.
Add header guards.
Style overhaul, and clarify some comments.
Style fixes for main file. Also give a bit of informational output when running.
Specify namespace.
Set radius in initialization list.
Minor speedup.
Fix -Wreorder and simplify AllkNN type.
Fix merge failures.
Adapt to new NeighborSearch API.
Revert to older Armadillo syntax.
Allow the dual-tree traverser to be changed easily.
Refactor BinarySpaceTree to use instantiated splitter.
Make sure the tree doesn't split on the same dimension over and over again when there's a tie.
This wasn't actually mean split before. Now it is.
Oops, did not apply changes to other overload.
Count base cases and scores correctly.
Add a BoundTraits<> class for template metaprogramming.
Refactor to use BoundTraits. Remove nextDimension.
Fix memory leak and bug.
Add methods for counting distance computations.
Refactor LSH. Don't used squared distances.
Remove pedantic ;s.
Add midpoint split. This often produces better trees than mean split...
Use MidpointSplit by default.
Fix header guard.
Don't specify the exact type; that's superfluous.
When BinarySpaceTree was refactored, its traits were not.
Merge pull request #438 from jahabrewer/master
Adapt to trees that aren't just binary.
Remove self-flagellation; no longer necessary.
Only unmap if necessary.
Fix includes.
Fix centroid calculation for cover tree.
Refactor UpdateTree() to pass parent bounds.
Fix typo.
Remove debugging output. Cover trees work.
Fix unnecessary copy.
Fix include ordering.
Fix include ordering.
Fix unnecessary copy.
Reinclude dual-tree cover tree test for k-means.
Add new tree trait.
Document new feature.
Add new contributor.
Add new utility functions for coalescion.
Remove unnecessary debugging output.
Merge pull request #437 from sumedhghaisas/master
Refactor to use SFINAE for both constructors.
Refactor input a bit. We don't take dense matrices for CF.
Slight refactorization for speed.
When coalescing implicit nodes, be sure to rebuild the statistic.
Optimization: don't needlessly tighten point bounds.
Update children before pruning points.
Refactor to precalculate variances.
Refactor to avoid issues with empty cluster action refactoring.
Adjust to new EmptyClusterAction API.
Use a sane strategy for normalizing variances.
Don't give up if the residue is NaN or inf.
Oops, bad paste.
Make a note that feature-sign search isn't used.
Refactor EmptyClusterPolicy to use both the old and the new clusters.
Fix changed EmptyClusterAction API for the tests too.
Add another test to mean shift, which should cluster 4 Gaussians.
Format fixes for mean shift.
Minor/trivial speedup: preallocate the matrix.
Update documentation, and fail on invalid algorithm.
Update code style.
Switch to residue termination, because it's *much* faster.
Print iteration and residue for tolerance termination.
Add as-of-yet untested termination policy.
Add tests for MaxIterationTermination.
Add MaxIterationTermination to list of files.
Add Index(), and make convergence occur for all iterations after the maximum iteration.
Refactor CF program to allow specifying the maximum number of iterations.
Time the factorization.
Allow the random seed to be set.
Switch to random Acol initialization by default.
Include acol init.
Use correct signature.
Merge branch 'serialize' of https://github.com/rcurtin/mlpack into rcurtin-serialize
80 columns max.
Merge branch 'rcurtin-serialize'
Remove SaveRestoreUtility.
Remove libxml2 dependency (awesome!).
First pass at Serialize().
Remove hmm_convert, since boost::serialization makes it unnecessary.
Remove old load/save utilities.
Remove save_restore_utility*
Refactor serialization shim to handle static methods.
Don't include SaveRestoreUtility.
Remove Save() and Load() calls.
Remove tests for SaveRestoreUtility.
Add Serialize() to KMeans and related classes.
Add Serialize() to GMM and refactor to not use references.
Add (mostly empty) Serialize() methods to classes related to GMM.
Refactor main program to use boost::serialization for saving.
Remove deprecated conversion utility.
Allow default construction, and fix syntax for Serialize().
Remove gmm_convert from list of targets.
Refactor HMM programs to use boost::serialization.
Fix particularly subtle bug that tried to free statically-allocated memory.
Alias properly.
Fix type error.
Refactor GMMTest for boost::serialization.
Refactor HMMTest for boost::serialization.
Remove unused bool.
Allow access to 'naive'.
Minor style fix.
Fix typo in documentation.
The beginning of a document about the TreeType API.
Fix somehow truncated comment.
Remove some crufty unused functions from BinarySpaceTree.
Add policies/ to Doxygen output.
Refactor to use Center() instead of Centroid().
Use Center() instead of Centroid().
Refactor to use Center().
Re-add Center() to the API.
Fix typo (thanks Ryan Birmingham for pointing it out).
Add a constructor that takes ownership of the data.
Remove stray space.
Update Doxyfile generation and list of trees.
Merge pull request #446 from trungda/trungda
Fix linkage discrepancy that produces a clang warning.
Compress if statement.
Apply Marcus' suggestion for better template template parameter template parameter names (that sentence is not redundant).
Add new contributor.
Add documentation for tree typedefs.
We transitioned from svn to git a long time ago...
No need for non-functional @defn command.
Fix some non-compiling Doxygen Latex documentation.
Fix weird formatting.
Add a Predict() method to LARS.
Allow passing a row-major matrix to Predict() to save time.
Add option to predict values on test points.
Mark down the changes I made to lars.
Include stdexcept (compilation fails on gcc 4.7 without this fix).
Update obsolete reference to svn trunk.
The collaboration graph is confusing. Disable.
Reduce namespace cruft in output.
Hiding scope names has a bug: https://bugzilla.gnome.org/show_bug.cgi?id=676971
Document the MetricType policy.
Make sure doxygen picks up info on typedefs.
Reference the MetricType documentation where possible.
Add an actual example.
Add documentation for the KernelType policy.
Do some documentation refactoring.
We use C++11 now; update the comment.
Switch to struct to be in line with other trait structs.
Revert "Switch to struct to be in line with other trait structs."
class instead of struct.
Make build directory Doxyfile update itself when root Doxyfile changes.
Document TreeTraits.
\b -> **, \e -> *
Compile in non-debug mode for faster tests.
Feel-stupid moment of the day: these unintentional loops have been here for months, causing tests to fail, which I never investigated.
Add Serialize() (unimplemented) to the perceptron.
Refactor perceptron to not modify input dataset.
Refactor weight vectors to be column-major.
Simplify expression.
Split biases into separate vector (speedup).
Fix bug introduced in previous commits.
Rename weightVectors to weights and simplify API.
Refactor to make instance weights optional.
Rename iter -> maxIterations.
Require specification of number of classes.
Merge pull request #450 from thirdwing/master
Fix Adaboost executable for Perceptron API change.
Add non-training constructor and write Serialize().
Add Load() overload with DatasetInfo.
Refactor perceptron program to load/save models.
Add Serialize() to LogisticRegression.
Wow, this was an incredibly stupid bug.
Refactor LogisticRegressionFunction to work with arbitrary matrix types.
Refactor so that OptimizerType is only needed sometimes.
Add and implement Train() methods.
Refactor logistic_regression to allow persistent models.
Add another Train(); remove templated constructors.
Add tests for new LogisticRegression functionality.
Refactor main executable. Still needs documentation.
Note the changes that have been made.
Update documentation for logistic_regression.
Fix bugs in logistic_regression.
When the user requests single-tree, actually do it.
Implement the Gini impurity.
Add tests for Gini impurity.
A base class for information after the split has been made.
A pass at VFDT implementation.
Simple tests for the HoeffdingCategoricalSplit.
Incremental check-in so I can work from a different system.
Make NumMappings() const.
Fix build with newer Boost versions.
New boost versions don't take kindly to comparing DatasetInfos.
Fix compilation with newer Boost on OS X.
Actually create the correct number of children.
Add Range() to GiniImpurity, and test HoeffdingSplit.
Clean up Evaluate() and fix test.
Use explicit mlpack namespace.
Fix test input.
Make sure training propagates through the tree.
Refactor so that dimensionality is a parameter.
Deal with newer Boost versions nicely.
Fix unused parameter warning.
Handle empty datasets.
Add Train() functions to NeighborSearch for consistency.
Test empty NeighborSearch objects and Train().
Add unfinished serialization test.
Add empty Serialize() methods to initialization policies.
Add Serialize().
Fix AllkNN serialization test.
Include std::vector serialization support.
Refactor to add Train() and empty constructor.
Refactor tests for changed NBC API.
Refactor for new NBC API. Not yet tested.
Fix incremental single-point training.
Add tests for Naive Bayes classifier.
Merge pull request #456 from stereomatchingkiss/softmax_enhance
Style fixes. Remove constructor that takes a file.
Add test for new constructor, Train(), and fix compilation error.
Add tests for new Train() functions.
Add serialization test for SoftmaxRegression.
Add new contributor.
Add separate Train() method.
Merge pull request #457 from stereomatchingkiss/softmax_enhance
Minor syntax and formatting changes.
Make sure that we don't run out of samples.
Set majority class when making children.
Refactor main executable.
Mild refactoring; Split() instead of CreateChildren().
Eliminate redundant classCounts.
Add (unused) test set parameter.
Avoid copies of dimensionMappings.
First pass at serialization.
Backport unordered_map serialization from boost 1.56.
Revert syntax for older Armadillo versions.
Fix include for typedef.
Don't set MLPACK_USE_64BIT_WORD when on a 32-bit system.
Add serialization to DTree.
Merge branch 'master' of https://github.com/mlpack/mlpack
Fix failed merge.
A first pass at a better numeric split.
This appears to be a failed merge; fix it.
Refactor so holding a dataset internally is possible.
Add Serialize() to CoverTree and tests too.
Remove using declaration.
Minor style fix/change.
Refactor to hold dataset internally (for serialization).
Serialization for RectangleTree. Not working---committed in order to work on another system. Also has debugging output.
Refactor Serialize(); don't duplicate the parent.
Remove debugging output.
Clean up memory afterwards.
Remove unused field.
Refactor to avoid duplication of root during serialization.
Don't check localDataset because sometimes it is NULL.
Fix uninitialized values.
Allow specification of dimensionality.
Sometimes the template recursion during builds goes very deep...
Re-initialize DatasetInfo on load.
Fix backwards initialization.
Don't save observations we haven't seen yet.
Fix tests that rely on DatasetInfo.
Smarter serialization; modest size decrease in output.
Only serialize the necessary split.
Shorten names to reduce file size.
Refactor to use template template parameters.
Allow large speedups by not requiring split checks every training point.
Add support for the BinaryNumericSplit.
Add access to the reference set.
Add a helper class for knn model saving.
Fix extraneous template parameter list.
Add move constructors.
Test move constructors.
The minimum Armadillo requirement is now 3.6.0.
Add rvalue reference constructors.
Add rvalue reference constructor.
Fix casting error.
Make some test sets smaller for speed.
Fix mappings for rvalue reference constructors.
Add std::move constructor for datasets.
Use rvalue references to prevent copies.
Update test API.
Fix initialization.
Handle zero-size cover trees... sort of.
Complete refactoring of allknn program.
Give name of tree in output.
Add ball tree support to NSModel.
Fix -Wunused.
Add 'ball' option for -t.
Fix definition.
Fix grammar issue.
Fix function signature.
Refactor allkfn program.
Fix tests to new API.
Merge branch 'vfdt' of https://github.com/rcurtin/mlpack into vfdt
Fix for new DatasetInfo API.
Split correctly on comments too.
Add a harder ARFF test.
Allow access to number of base cases and scores.
Initialize baseCases and scores correctly.
Allow ownership of data matrix.
Add Serialize().
Minor style fixes.
Serialize number of classes correctly.
Fix invalid accesses by reordering loop conditionals.
Use a const datasetInfo.
Fix #464: the assert was not valid.
Comment the HoeffdingSplit class.
Add some documentation (finally).
Refactor: HoeffdingSplit -> HoeffdingTree.
Fix names of constructor/destructor.
Fix -Wreorder.
Update include paths.
Add (unimplemented) batch training functionality.
Remove unnecessary dimensionality parameter.
Use Row for labels.
Slightly better documentation.
Fix API; prepare for deletion.
Remove StreamingDecisionTree; refactor main executable.
Update configuration.
Refactor HoeffdingTree to replace StreamingDecisionTree.
Take ownership of DatasetInfo struct when needed.
Don't use StreamingDecisionTree anymore.
Refactor tests for new HoeffdingTree API.
First pass at batch training.
Add batch mode and a test for it.
Add batch training option.
Update documentation.
Add a function to create a random basis.
Fix documentation.
Add move constructors and Train() functions.
Add Serialize().
Add RSModel (not yet tested).
Fix formatting.
Fix casting issues.
Add tests for Train() and move constructors.
A better attempt at batch training.
Add separate split info for binary splits.
Make sure the split improves things.
Clarify where splitting actually occurs; fix bugs.
Fix tests for changed APIs.
Make query set a parameter to Search().
Add Serialize() for RASearch.
Serialize all search preferences, not just some.
Check for correct neighbors correctly.
Add minSamples for splitting.
Add information gain and tests.
Fix -Wreorder.
Add flag for using information gain.
Make children pointers, so serialization doesn't copy dimensionMappings and datasetInfo.
Refactor EvaluateFitnessFunction().
Refactor for changed EvaluateFitnessFunction().
Fix -Wuninitialized.
Remove extra space.
Merge pull request #466 from stereomatchingkiss/softmaxExe
Minor style changes; no functionality changes.
Merge pull request #472 from Kirizaki/master
Tiny minor documentation changes.
Add new contributor to copyright list.
Move timerState to Timers, instead of the static Timer class.
Add breaks in switch statement.
Serialize tolerance and initial states.
Use CLI parameters correctly.
Add the number of passes to the program.
Make parameter name unambiguous.
Handle non-new DatasetInfo objects better.
Actually take multiple passes over the data when streaming.
Yes, this is the problem I've been chasing for weeks.
Check the feature size.
Use Row, not vec, for predictions.
Refactor main program, add documentation, slightly improve functionality.
Add changes to HISTORY and document new program.
Issue a warning when observations are not given for all classes.
Fail when invalid labels are specified.
Fix #478 and add tests.
Use a pointer to the reference set, so it can be changed.
Add Train() method.
Fix typo.
Handle the k == 0 case without crashing.
Add empty constructor.
Add some accessors to internal LSH fields.
Fix ownership bug: we don't own when we Train().
Add some warnings, and make some minor fixes.
Add Serialize() and test for LSH.
Test the empty constructor.
Merge pull request #481 from arnike/master
Force re-Precalculate() when we run out of points in one cluster.
A smarter splitting criteria that works right.
Merge branch 'vfdt' of http://github.com/rcurtin/mlpack into vfdt
Add min_samples option.
Print test and training error.
arma_config.hpp is auto-generated; don't keep it in the repo.
Remove build artifact.
Formatting fixes.
Revert DETTest.
Open .bin models in binary mode on Windows.
Add new contributor.
Don't transpose columns on save (#484).
Merge pull request #465 from stereomatchingkiss/visualizeEncoder
Cast to fix std::min() call.
Rewrite and elaborate on documentation significantly.
Fix -Wreorder.
The positivity check is unnecessary -- it's a size_t.
Fix -Wreorder and provide better documentation.
Document what the file is.
Standardize terminology.
Refactor main program to allow saving/loading LSH models.
Update history for LSH changes.
80-column maximum.
Refactor DecisionStump significantly.
Add serialization to DecisionStump.
Always resize the labels vector when Classify() is called!
Clarify or fix documentation for API changes.
Add tests for empty DecisionStump constructor and serialization.
Change 'attribute' to 'dimension' for consistency.
Refactor decision_stump to allow saving/loading of models.
Remove superfluous semicolons for -pedantic.
Style and documentation consistency fixes.
Refactor AdaBoost constructor to allow default parameters.
Add Train() and a test for it.
Make tolerance private; add accessor/mutator.
Initialize size of predicted labels correctly.
Performance improvments.
Don't use finalHypothesis.
Remove unnecessary BuildWeightMatrix().
Code and speed cleanups: make things column-major, etc.
Fix segfault.
An optimization to speed up the binary split -- but it's still slow...
Merge pull request #488 from Kirizaki/master
Trivial style fix.
Clean up documentation.
Minor style fixes.
Add file header.
Braindead refactoring strikes again.
Add error handling when streams fail to open.
Be more clear with error message.
Remove data and codes members from SparseCoding.
Refactor so only the training is templatized.
Use double, not size_t.
Fix Classify().
Refactor tests to avoid finalHypothesis; use Classify() instead.
Remove finalHypothesis.
Add some more documentation.
How did I forget to add Shangtong to the list of contributors? :(
Add empty constructor, rvalue reference constructor, and tests.
Add Serialize() and other accessors.
Allow this constructor to be a default constructor.
Test Serialize(). Clean up test, too.
Refactor serialization tests; add SparseCoding implementation.
Remove tab character; reformat.
Syntax fix.
Add RAModel.
Add test for RAModel. (does not yet work, still debugging)
Remove tab character; reformat.
Syntax fix.
Add RAModel.
Add test for RAModel. (does not yet work, still debugging)
Issue an error if config.hpp is not found.
Print the number of nodes in the tree.
Use Row instead of Col.
Use Row instead of Col for labels.
Reorder template parameters for consistency.
Refactor main executable. Allow saving models.
Fix transpose issues.
Add default parameter.
Fix transpose issues.
Add Serialize() to SparseCoding.
Move Serialize() to _impl file.
Add model save/load support to sparse_coding.
Rename OptimizeCode() to Encode().
Merge pull request #492 from MooNDeaR/patch-1
Merge branch 'no-to-string' of https://github.com/rcurtin/mlpack into rcurtin-no-to-string
Merge branch 'rcurtin-no-to-string'
Add new contributor.
Make lines 80 columns wide.
Merge branch 'master' of https://github.com/mlpack/mlpack
Merge branch 'master' of https://github.com/mlpack/mlpack
Okay, so it turns out I'm not very good at git merge.
Remove unnecessary includes.
Remove extra line.
Fix documentation typo.
This constructor actually does not initialize the dictionary.
Remove unnecessary parameters.
Finish transition to Row<size_t> for labels.
Refactor LCC to same API as SparseCoding.
Merge branch 'master' of https://github.com/mlpack/mlpack
Add _impl.hpp file and serialization.
Refactor lcc program.
Better casting, remove std::.
Add additional parameter validation.
Rename Estimate() to Train().
Rename Estimate() to Train().
Update documentation and use Train() not Estimate() for distributions.
Update tests to use Train().
Use Train() not Estimate().
A smarter strategy for checking positive-definiteness.
Fix syntax.
Refactor GMM: only use FittingType template parameter for Train().
Add more useful GMM programs.
Update lists of programs.
Use right call to chol() depending on Armadillo version.
Relax tolerance for test.
Loosen tolerances to reduce failure rate.
Loosen matrix tolerance checks a bit for floating-point errors.
Relax tolerance.
Shangtong Zhang (1):
add can network
Siddharth Agrawal (15):
Removing old cosine_tree code.
Adding new cosine_tree code.
Combined CosineNode and CosineTree classes.
Adding QUIC-SVD.
Removing files added by mistake.
Removed a few tabs.
Adding Regularized SVD Code
Adding tests for Reg SVD.
Made Reg SVD work with CF.
Minor documentation changes in CF.
Added code example for Reg SVD.
Added QUIC-SVD code example.
Added Reg SVD to CF executable.
Added help information in CF executable.
Adding Softmax Regression module.
SreudianFlip (1):
commit 2a96324ffd3fb514184a32a6e8c1c95e8b13fcc4
Stephen Tu (100):
WIP: first cut at sparse LR-SDP solver
remove superfluous inline
Rename variables to be consistent with rest of codebase
fix compile errors
fix bug in test initialization
temporary hack: remove the last edge constraint
don't hardcore Evaluate for the lovasz theta objective function
add small max-cut test case
use a better starting point than all ones
Merge remote-tracking branch 'mlpack/master' into testcase
Add matrix sensing SDP test case
cleanup sensing test
Use a deterministic starting point for max-cut test
First cut at matrix completion method implementation
Add matrix completion test case
Comments
add comments for sensing SDP test + remove redundant data
Merge remote-tracking branch 'mlpack/master' into testsensing
don't let the compiler infer matrix result types
Warn if ratings of 0 are found
Address some stylistic issues
move matrix_completion_impl.hpp to matrix_completion.cpp
only use PGO when compiling with GCC
WIP: a compiling, but non-functioning primal-dual IP SDP solver
WIP: a compiling test case
WIP: hammer out a few bugs, still doesn't work
WIP: fix a few more bugs
add a check for dual feasibility
WIP: commit missing data file
restructure the primal-dual tests a bit
error checking of initial matrices
lovasz theta SDP test
Add log chebyshev approx testcase
add a comment on why the MVU test fails
comment out MVU test case
add correlation coeff sdp test from wiki
minor cleanup of comments
Add some comments/TODOs to the primal-dual implementation
distributions now offer LogProbability() in addition to Probability()
WIP: gaussian distribution caches covariance factorizations
WIP: fix one test case
fix some distribution test cases
some more distribution test fixes
ensure random covariance is positive definite
fix HMM load/save tests by ensuring covariance is positive definite
remove stray commit
implement the mehrotra's predictor-corrector rule
refactor KKT solver
more refactoring
sparse svec
primal dual method now takes adv of sparse constraints
use glibc constants
make the SDP objective matrix type a template parameter
iteration check is now iteration != maxIterations
Port LR-SDP to use the new SDP problem object
fix up PrimalDualSolver::Optimize() return value
Merge remote-tracking branch 'mlpack/master' into ip
invert the lower triangular matrix the right way
remove unused variable
expose SDP object directly for LRSDPFunction
use builtin diagmat
Inline alphahat into alpha
iteration=1 to allow maxIterations=0 to work
some comments for the algorithm implementation
Add a relative objective value termination criteria
Set the default starting penalty to 10
add back missing edge constraint
Add matrix sensing SDP test case
add comments for sensing SDP test + remove redundant data
Update naive_method.hpp
Update naive_method.hpp
older versions of arma do not support unary minus on sparse matrices
cov matrices should be symmetric- fixes error in gaussian test case
Comment out SDP test which is failing randomly
SDP primal-dual: use a more numerically stable starting point
iterator counter was off by 1
WIP: test out this travis.yml
travis.yml: add armadillo dep
travis.yml: maybe this will let us get the right version of arma?
travis.yml: add libboost-dev dep
travis.yml: add a newer version of boost
travis.yml: hopefully this includes all the relevant boost libs
travis.yml: cat arma_config.hpp for debug
travis.yml: we really want config.hpp
travis.yml: add custom config.hpp
travis.yml: don't die when diff reports diff
travis.yml: i hate you
travis: try ARMA_64BIT_WORD
travis.yml: make test
travis.yml: pwd for debug
travis.yml: log level all for tests
travis.yml: try travis_wait
travis.yml: don't use travis_wait
arma::inplace_trans is not available for older versions of arma
Remove un-necessary string copy for GetTimer()
Cleanup: remove trailing whitespace in source files
Merge pull request #419 from stephentu/master
fix unused parameter warning
add notifications to travis.yml
the CMake flags are newline sensitive
Sterling Lewis Peet (81):
setting up build server packaging scm directories
[svn-inject] Creating hudson/tags/ directory.
Creating trunk directory
[svn-inject] Applying Debian modifications (1.388-1) to trunk
final hudson packaging cleanup
[svn-buildpackage] Tagging hudson 1.388-1
corrected mistake in README
[svn-inject] Creating jenkins/tags/ directory.
Creating trunk directory
[svn-inject] Applying Debian modifications (1.415) to trunk
update jenkins package rule get-orig-source to put the tarball in the tarballs folder if it exists
original source tarball for packaging jenkins
comment out unused file installation
svn-bp:origDir property allows svn-buildpackage to figure out where the original source tarball is found
[svn-inject] Creating armadillo/tags/ directory.
Creating trunk directory
[svn-inject] Applying Debian modifications (1.2.0+dfsg-0ubuntu1) to trunk
Fix dmangle to properly convert the local version of the package to the upstream version format
Update README for debian packageing to reflect the correct way to call svn-inject for this repository and add a note about how to make obtaining the original source tarball easy.
runTestBins.sh runs all the test binaries, finds boost test results, then renames those results for jenkins to pick up for test result reporting.
Remove svn-buildpackage artifacts mistakenly committed to the repository
Update watch file to use new jenkins war file packaging script
Modified jenkins package changelog to reflect our packaging situation
update maintianer address in control file to comply with debian standards
update maintianer address in control file to comply with debian standards
Update jenkins packaging to more closely match upstream packaging
Tagged from Package-Jenkins #27. Jenkins package is successfully being built but still has some lintian issues. Does not grab the plugins yet, nor does it automatically build a new package from a new upstream release yet.
wrapper script to convince jenkins not to mark the upstream source checking build as failed because there are no new upstream changes
forgot to make uscan-wrapper.sh executable
Strip non-XML compliant charachters from the test result files before xUnit pukes on it
Remove non-sed compliant option from the regex string
Tweak script output to make determining Unstable build condition more reliable
Replaced sed with more appropriate tr invocation
another fix for uscan-wrapper
[auto-packager] updating packaging to reflect new upstream release
Fix update made by buggy script
new automatick packaging updater script
[auto-packager] updating packaging to reflect new upstream release
Tagged from Package-Jenkins #33
Fix some lintian complaints about the packaging
script for generating the sloccount results
fix output file
only run sloccount on the library, and not the contrib
remove line that was meant for testing only
new post commit hook to notify build server of repository commits
fix report directory collisions
auto-packager updated to use a secret file on the build server for subversion access
remove debug lines
next rev for jenkins package
Tagged from Package-Jenkins #35
increased script robustness
fix authentication problem, i hope; it worked fine on my machine.
fix issues with interactive prompting in a non-interactive script
fix another issue with interactive prompting in a non-interactive script
fix typo that broke the script
don't fail out of svn-upgrade ust because it can't perform its own _svn up_, because the script just did that
Add some notes and changes, functionality does not change but I can debug from another machine
convert to uscan/sed/awk/dch instead of using svn-upgrade
make the rquired directory if it doesnt't exist
add forgotten $ symbol
fix build hang when calling dch
allow auto-packager to update the repo, now that it appears to work
[auto-packager] updating packaging to reflect new upstream release
Tagged from Package-Jenkins #47
[auto-packager] updating packaging to reflect new upstream release
Tagged from Package-Jenkins #48
Tagged from Package-Armadillo-stable #10
Update to upstream version 2.0.2
Actually use the DATA_DIR after making it
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
Tagged from Package-Jenkins #50
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
[auto-packager] updating packaging to reflect new upstream release
update version and soname
TrironkKiatkungwanglai (13):
I added in logic to remove duplicate flag parameters in response to Ticket #231.
#164: Any objects passed into a prefixedoutstream that contain a std::string ToString() const method will write the results of the ToString method instead of simply being passed directly into the prefixedoutstream.
#164:
Added more documentation to sfinae_utility.hpp.
#147
Implemented the ToString SFINAE pattern.
Implemented ToString methods for the math folder.
Working on implementing the ToString functionality for the tree folder - getting a seg fault with the cover tree class.
Implemented tree folder ToString methods. Anything involving a mrkd_statistic, binary_space_tree, and cover_tree are encountering segfaults with when they are being destructed, though.
Abbreviated the Range ToString method to return one line.
Resolved tests to compile with ancient versions of boost.
Standardized code style for DiscreteDistribution's ToString method.
Initializing MRKDStatistic's leftStat and rightStat fields and standardized cover_tree/cover_tree_impl.hpp
Trung Dinh (1):
Fix build failure with clang.
Udit Saxena (31):
Decision Stump added
Fixed armadillo issues, along with removing uninitialized and unused variables
Perceptron Added
Decision Stump test fixed
Rewinding the code review
Fixed subvec calls.
New test added. Improved entropy calculation.
Entropy calculation improved.
IsDistinct() improved.
Changes are part of perceptron code review, as discussed with Ryan
Minor improvement. No major functionality changes
Minor updates
Adaboost design issues, to be discussed, then changed later on
Minor changes
Minor changes to the macros in the *main.cpp files.
Adaboost and Perceptron modified (improved constructor), going for tests on one Weak L
Changes to implementation of adaboost. Implemented adaboost.m1
Adaboost.mh implemented
BiBTex added to adaboost_impl.hpp
Adaboost improved. Tests for the UCI iris dataset added.
Adaboost test improved and now works. Improved adaboost.
New tests added for adaboost.
More tests for Adaboost added, with tolerance for change in rt also provided.
Adaboost now works with Decision Stumps; added tests for the same and extended tests for Perceptron too.
Refactoring and optimizations on Adaboost.
Decision Stumps modified, along with adding Classify() function to AdaBoost. Other minor changes (renaming).
Changes to Decision stump and AdaBoost.
New tests added for the AdaBoost classification function.
Style changes. No code changes
Comparision-type warning sorted out.
Tests updated and new datasets uploaded.
Vladimir Glazachev (4):
Adds inplace transpose method and some tests. This method used in Load() now.
inpace transpoce moved to load_impl.cpp
use std random module instead of boost
added vim temp files to gitignore
Yash Vadalia (3):
Incorporate patch from yashdv to move splitting procedure to a different class.
Contribution from Yash to solve #250 and make BallBound usable.
Tests for ball trees and BallBound<> by Yash, to solve #250.
abhimanyu (17):
Checkpoint1 contains the pointer based implementation of tree creation without storing the tree in the database. The tests seem to show correctness. The Euclidean distance functions have not been tested.
This is check point1.
This checkpoint introduces median computation into the system.
Changes:
This is the first working version of dual tree nn. It also includes the master sql table and things like that. dual is working and seems to be giving correct answers for a few random tests. it needs to be optimized for its taking about 1.5 secs for 5000 queries :(.
This is the tested correct Parallel KD tree construction.
This is the tested correct Parallel dual tree as well as parallel KD Tree construction. Now only code cleanup and commenting is left. Also implement the file write and read option.
Pointer based Dual NN. Is working correctly for single tree. Runtime for 400k points is about 16 seconds.
This is the final. All file functions have been tested. They are good. Now just clean up a little.
commit b01837dc4fc88f68d1ea0d7ca074638b5112cc5d
commit 12938cacdafd1830de840dcac7282e5a31805446
commit fe34bc360970cd836d75ae3e778ea18a592104cb
commit be4bc6a1b9f7d1272fec1eb87e53233ef88f92b9
commit 28a2fe0db058a944d5f48c67d3c25fc83042eb2b
This checkpoint introduces median computation into the system.
Changes:
commit f4d2bd0131c0257a727fab56ed729d3fe7bd7ca0
agray (1):
changed chapter 1
andrewmw94 (58):
Add files and some preliminary code for R tree
readability changes to BinarySpaceTree::FurthestPointDistance()
added more code for the rectangle type trees
remove the silly folders I added when I meant to add txt files.
now add the actual files the way they are supposed to exist. No real code yet.
added comment to base case. Some more preliminaries for rectangle trees.
add a short and hopefully useful explanation of what different files are for, focusing on BSP trees.
add a description of statistic
more code for the RectangleTree. Still not built yet.
more R tree stuff. Still no build
more R tree stuff. Still no build
more R tree stuff.
more stuff for R Trees
more R Tree stuff
R tree stuff
added code for accessing immediate child nodes (need to think of a way to rename this to be less confusing). Some more quasi-code to split nodes and insert points.
Fix/update some comments, almost finish the splitting algorithm. Several miscellaneous changes.
change name of leafSize to maxLeafSize. more stuff for the R-tree. Some name changes, some more node splitting, a start on traversal.
a few miscellanious small changes. Added to CMake.
add the missed files.
require kd-trees to have leafSize of at least 1. Add an assert to ensure that the SingleTreeTraverser isn't called on a tree with only one node.
Rectangle Tree Traversal implementation.
change a comment to be more accurate. Add on --r_tree option to the knn_all program. Doesn't do anything yet.
comment out compilation. Some small changes to support R tree in all_knn
fixed some mistakes. Still commented out to allow build.
more fixes. Compilation still commented out.
more of the same.
More bug fixes.
more bug fixes
keep the root node at the same address.
bug fixes
bug fixes for memory leaks
bug fix. had n_rows when I needed n_cols
Rectangle tree and tests. Construction seems to work.
memory leak fix
change the tree to store size_t in the nodes and keep the dataset together. Other misc changes.
rectangle tree traverser
fix build
commit to ease debugging
work arround for CMake bug.
tree traversal
R tree traversal test code.
R tree now has dataset and indices
Point deletion. Massive refactoring of Children()[i] to Child(i). Really minor point deletion test.
more tests. Really silly bug fix.
point deletion. bug fix. more detailed test.
R* tree split and descent heuristic.
R* tree split. Default to using the R* tree in allknn
Bug fix. Node splitting tests.
R* tree bug fixes.
code cleanup for R tree
R tree clean up. Change Child() to match BSP tree. Copy constructor takes a second argument to specify whether it is a deep copy.
Point deletion bug fix.
X tree commit
X tree
Dual tree traverser.
dual tree traverser bug fixes.
Dual tree traverser bug fix.
angi (25):
Initial version of n-point. Contains code for matchers, metrics and naive n-point plus a few handy datasets for testing.
Minor improvements to the metric and matcher plus new utilities for the general multi-matcher problem
Removed datasets
extra info
commit 94939288246d967a4aef2d8e2266c7c9f1b57348
commit fbf9aa21812e79477817cc507a12a946f769abd5
commit 3e99cdfbae3b0e9986551c85eac8315330dce027
commit 4841686d0b01a45ef025d39c6a70bddd60bb92c5
commit 016699c78c77e9e58b74707dc7f73bdbea4dee23
commit 734594d858765c5cdb13b8771efc688ba751473c
commit 5120ad330c3740793f9636819e54dffc96a0aca4
commit a86bd06b5de228f726044685cccf09ec54558e92
Fully functional weighted and unweighted naive npoint.
added auton npt
commit 57c77373bb636ba8836f88c1764d81be2d2d8784
commit b720d927db98939629062a0a3be9e8065868e326
commit ddec7afe8246c77e50b8e47abfd08bfc2f00ac42
latest debugging version of auton npt
commit 9854ec3103559a9a735e5a40d0b5e2f9462723ab
commit 4ae53b9718f0d721024bd97ebfb0ba6bc519d4cb
partially debugged npoint
commit 7b7c2f4a4ef47731a6fb2e93c2bd2bbfac60a571
commit 9e849f0ba6380744aff1ebdaeee23cb1789fdd2e
commit 7deca9b87fac110833f2766168f54f4c0702a573
commit 6a97374573586c7e7d8b2d50f95df16670248366
apir8181 (2):
better boost test output
add intercept term to softmax regression
archana (2):
added archana's code
Added a sample datafile
arkadas (4):
This will be used for proposals.
Added brinson proposal
created for my tex files
working on wedgeHF
ashish (11):
Added PLDI 2009 paper.
Minor updates to PLDI draft.
Added several new modules, and INSTALL, README, and Makefile.
Minor update to Makefile.
Added prerequisite information to INSTALL file.
Rearranged and added several files.
Implemented build system.
Fixed conflict with my working copy.
Added Lines module.
Added About module.
Added About module.
birm (30):
Added ToString() to core/dists, core/kernels, and core/metrics
Updated Test for working optimizers
Added Tostring to SGD.
Addes Tostring here early, mostly because SGD required it.
Changed so that "dimension" is not declared, to avoid compiler warning.
Changed so that "numPrunes" is not declared, to avoid compiler warning.
Added L_BFGS
Added ToString to LBFGS
Fixed AugLagFunction Test; working on AugLag proper.
Added ToString method
Added ToString for AugLag Itself.
Fixed AugLag Test
Fixed my own error in ToString of AugLagrangian
Fixed Test Error
The Problem was the Test; Added ToString to AugLag's Test.
Added BallBound ToString test.
Fixed Positive Def Constaint under gmm; previous error was "/gmm/positive_definite_constraint.hpp:28: error: expected primary-expression before ‘(’ token" at lines 27 and 33.
Added ToString to GMM
Some ToString added, some updated (typos and indent). Test updated.
Fixed my subversion error, hopefully.
Fixed a Mistake in HMM's ToString
Added and Modified more ToString methods.
Modified StringUtil to take a number on Indent, implemented LSHSearch ToString, updated Test.
Added more ToString, updated test, took advantage of new tab function.
Finished toString of the methods folder ( sparse coding and rann ); updated test.
Updated Test and pspectrum_string_kernel
Updated Test and some info for ToString.
Fixed arma_traits by removing duplicate template instantiation, so that visual studio would be able to use it too.
sparse_autoencoder_function lines 55 through 58 modified so it would build. It doesn't pass the test, but it builds now. Please fix.
Added check to solve ticket 347. Note that this does not changeany functionality, just adds a warning.
cmappus (7):
infomax ica code
update fix for the change to SetDiagonal
updates to align with style preferences
edits to align with style preferences
edits for aligning with style preferences, convergence threshold stopping feature
infomax_ica updates for fastlib2
more infomax_ica updates for fastlib2 release
gcolon7 (13):
Changed calls to math::Pow and math::PowAbs to std::pow and std::abs
Changed math.h to cmath, math::Pow to std::pow, and math::PowAbs to std::pow and std::abs
Change 2 to 2.0 in divisions to enforce float division
changed math::Pow to std::pow and math::PowAbs to std::pow and std::abs
changed optimization_utils.h to std::pow
changed lbfgs_impl.h to std::pow
removed math::Pow and its relatives
This contains the implementation details for the deprecated math::Pow and family
added <cmath> to the list of general includes in fastlib.h to provide for methods such as std::pow
Fixed optimization/lbfgs/lbfgs_impl.h & optimization_utils.h so that they use std::pow instead of math::Pow. Also added a cmath include in fastlib.h
Missed a math::Pow to std::pow in optimization/lbfgs/optimization_utils.h
changed math::Pow for std::pow wherever it was called in the mlpack and contrib directories
Undid a horrible mistake
gmravi2003 (177):
made my home directory
Added allknn directory (initial checkin)
commit 45b884baee9b9936c2819c2c1a7624febe603f1d
initial checkin of allknn
commit 068ef7e4cfb0af0917a53aca050824572eb7706d
regression bugs still not fixed
removed main
buggy partial regression code
This code is working fine. It does B^T WY usin kd treesregression.h
This code is working fine. It does B^T WY usin kd trees. Made just a minor change wrt the previous version
Code is working, but is still not gold standard
This code is buggy. Looks like the inversion is not happening properly
Still buggy. Transformation is no working in regression.h
Perfectly working code
Buggy code. Trying to incoporate the order of permutation of the regression estimates
regression code. slightly buggy
buggy regression code. Segfaults during tree formation
regression code sligtly buggy. faults at tree construction
buggy regression code. faults at tree construction
working code
build file
commit 9b1aaa78085375654d83441c03700699d7fe3f94
fully working regression code. TRake care of permutations of regression values now
regression code. Perfectly working about to incorpate NWR stuff
regression code. Perfectly working about to incorpate NWR stuff
These files are perfectly working. Will now incorporate code to run executable multiple times
Fully working files
Slightly buggy
the partial main file for the new regression code
commit 2438aa8d39f0e881e839decefc2d332c3c4a2b77
Working. Will now add B^TWY code
Working B^TWB code
data file
commit 604173ea10e0c4fd7d5d2f98ed3326cb6f367f4b
data file
build file
commit 5fe779ac3cf0a0f2161b40628241a355f4d050af
commit 535e9f2b683130c140bbd9bdea507cb4e6f6e2a2
working cde with comments
commit 95ed1ba0fa14b730c71e990fcd505c9f0d9aeeac
commit c1ced13f719c84cbb9ca006fdfe9afdb71198d00
commit 782ceb28bd62f53dcf7d8957e71a4cde1e180a07
commit 0e0e13734cec83d34d391d8513993deb4f82d1d5
commit 80940aa0ae32b390ea4efde311ae5b46c5dfbb93
These are the files that have been thoroughly commented, for code review
commit a3181b37e9cb9c4d105f65a7445487067e16fd40
commit 5f557ed9d250ddaf1f3da62ae6ed6c1555db7f02
Fully commented oh i meant
Fully Commented and refurbished
commit 0756d748cef567617d0fe291d139c32fbcc7c70a
commit b276326e3d1a55bf35f8a1f61038a0c2f46261d9
commit 7199ee17ad96db34278b63f02092be7b2c809b96
commit c886f254b04c355eb2cad838f02fbbb9c2065179
commit bd99c4f2e9f4560fa544375450612571de3bb7af
These are fully functional files. Now I am about to change the code for component wise bounding
Partially completed diles
Partially complete codes
This code is buggy and incomplete though it works for tau=0 case
Complete code. Calculates BTWB and BTWY component wise. But still buggy
These files are perfectly working
SVD Code incoprorated. Will go on to write the frobenius norm pruning now
Perfectly working pieces of code. They do both component wise and frobenius norm pruning. Will add SVD now
SVD code incorporated. Fully working
This is the function which caclulates the pseudo inverse of a matrix by SVD
Buggy. Couldnt debug it
KNN Based regression. Confidence Intervals are still being added
Fully working without adaptive BW
Looks like working.Havent tested it completely
Looks to be fine
Partially complete code
partially complete
Complete. Will need to do a small final check
Fully working. However there are mem leaks
Slightly modified. Still workingb but with mem leaks
Fully functional. No leaks
commit fb24c64dd03a3076a3aae39612ddcc6ce599b152
density estimation usign erf kernel
Everthing is working. but has to be cleaned
Fully working. Need to make some more changes before I run full scale experiments
Tester file for special la
Predictor corrector main file
Repaired code
Fully written code, but still doesnt give desired results
Plain code. That is the code has hardcoded values for the vectors
Still not working, but better than previous version
Code before changing cholesky factorization to dynamic stuff
Code before changing cholesky factorization to dynamic stuff
Code before changing cholesky factorization to dynamic stuff
Working codes
Working codes
Working codes
Working code
Working code
commit 0d83d082f0fa2582d1d77bfd00113bab7300bb23
commit 7494bc09ec9bf7ad5e17865425486e4e9f9a58a4
build file
Fully working code
Fully working
commit 4f635067087c11d850e467e9e06ec3fe5294f5dd
code written as per smola's book
Dont remember if this is useful file. Nevertheless commiting it
all written as per smola's code. Will need to change
Performs incomplete cholesky by dynamically adding columns
This is the new file, with changes to interior point code
Working. Will now go on to change the starting point selection
Working. Will now go on to change the starting point selection
Working fine(atleast looks so). Will change stopping criteria
Working fine(atleast looks so). Will change stopping criteria
Fully working code for 1-D setup.
Fully working code for 1-D setup.
Perfectly work. Commiting before I make changes for multidimensional case
Perfectly work. Commiting before I make changes for multidimensional case
Perfectly work. Commiting before I make changes for multidimensional case
Perfectly work. Commiting before I make changes for multidimensional case
Perfectly work. Commiting before I make changes for multidimensional case
fsdfsdf
commiting after long time. Will add classification experiments
commiting after long time. Will add classification experiments
local kernel machines
commit 089bb18ef16496bd7ef33e63e5e4aa76e28dafaa
commit 73d59a9ddd5f5e8619d8bbb634164b9d7c05c718
commit 89a51c3b63dc612cdaf7279d28413528fe28ccf1
commit bbeb78a8d5a57bc04ca6e46503072f91dee6ab1e
partial
commit 626e898432537843795a309556f889f466f52924
commit a4626148e5f29b9108620286d0d78c93cdefb3e4
commit 61a948f0ff3f9659afdb85009478414b02988f1f
commit 16c21ac6b6c0c1bfd3fb89634ccee55c94c0ee0a
commit e1a35412b4566e41aef66b8945c799d0e564fa41
commit 96cc4f032dd9fffaa764b59f863cf0ac26ceedab
commit 8aa58e45466571c7d011f0297ef590d61880a316
commit aedbb764096f64de24463d1f60b49d29176e118d
commit 12f5ee4b9ecbdf673a49ff343f98abab50fd808e
commit d5fbf749ea74380e97721ed42f27f68c3ce1edc4
commit 15722a77d2d57a261a7e1c246862390358622c60
commit 5d27a2a3f11f00b42c4e1e584974459737f61c59
commit eef920730d618c0c2ba592b6a66505bcd4f7144e
commit bef179d655b8ea04391a35668df235b8dd57f156
relevant files
Working set of files
untested code
works for 1d
stil buggy
Seems to be working with a 2-d setup also. Need to test even further
Seems to be mostly working
Tested and certified 1
Tested and certified 1
Tested and certified 1
Tested and certified 1
Original version. Will make it simple
Tested and certified 1
original version
Looks working 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Looks fine 2.0
Working version 3.0
working version 3.0
working version 3.0
working version 3.0
working version 3.0
Not fully correct 4.0
Not fully correct 4.0
commiting before crash
commiting before crash
Seems to be working 5.0
Seems to be working 5.0
Mostly working 5.1
Mostly working 5.2
Mostly working 5.2
fully working
gtg931v (6):
1st commit of kalman
commit 0f0eef79f081d502b8a2d20b4a4acd67aa9c4a82
deleting old things
deleting old things
deleting old things
time invariant kf dated jan 23
hjiang (5):
first check in of jiang's directory
first check in
added 2 utilities to access the trees and made the tyupedef publicwq
Huijings code for getting the centroids and nearest neighbors
delete accidental insertion of a binary file
houyang (200):
commit 74df495c6671bf4eb8c2fccf41103ae07b5ae63d
Multiclass SVM classifiers, using SMO.
Multicalss SVM classifier
add a readme file to multiclass svm classifier
commit 80d71f2e2b267abddb253d9e2b0bfba62100e5c8
commit 6ebd4223e4c89bc731db577f3bca93860b9ca9bb
Add two functions:
build.py modified. minor bug fix in svm.h
fix bugs on model file loading
add toy data
bug fix for sv_indicators
add/modify docs, add 2 and 3 classes toy datasets
DOS's CRLF-> UNIX's LF
doc modify
final doc modify before freezing
commit 1cc18bf8e3a661e6250e58647ee1d28093df5a77
commit 85bdf9a69fe40cb0db3e7ef4ab768b22be1593ec
commit 45d581b7a488d9e3874b86dca54ac04dedbf351e
commit f849e3f7cdabaad022351e630b4370453118d484
Add a general cross validation class, which can be used for classification, regression and density estimation. Alpha Version. Still under construction.
SVM regression
Add a statistics module. More functions to contribute.
Relevance Vector Machine (RVM)
rvm classification
commit 0e9327bef9126ed005ce0a326c7176d805dffd75
commit 1203f4905e08258143a1988d00833f14421928d1
commit 72b6fc056a37ed3d118c1e8bc68a6805876c7e33
commit 0b15bc65c268417918dcf0762d0fdaf553ad3f4d
commit 0aa61016347f5edbd6b2d902054590bed213d7ea
fix bug in getlabels, delete (int)
commit 3a4232411f856692b5ff74e6a841262e9b1ce54b
Addback -> Addbackitem
bug fix in crossvalidation.h
In GetLabels(), all the input parameters are required to init beforehand. GeneralCrossValidator() is modified accordingly.
New SMO implementation. Support vector machine for regression now functional.
minor bug fixed in SMO
Shrinking, Caching added
minor bug fixed
CalcKernelValue_ updated
Add statistics module, more functions to contribute.
Add GeneralCrossValidator class which support k-fold cross-validation for classification, regression, density estimation and user-defined learners. Alpha version.
Move everything in my folder(houyang) from fastlib to fastlib2
Replace deprecated functions in crossvalidation.h and dataset.cc. Update svm code under mlpack with the updated version. It now supports support vector regression.
Replace deprecated functions in RVM with new ones.
update for fx_ functions
svm documents added (partially)
crossvalidation.h bug fixed
add solvers for general eigenvalue problems (for both symmetric and nonsymmetric matrices)
allknn_balltree and allknn_kdtree added, support single/dual trees
Add stochastic gradient descent optimizer for linear and nonlinear SVM classification
bug fixing for multiclass SVM based on opt_smo. New implementation for stochastic gradient descent solver for SVM: opt_sgd. Experimental codes for hierarchical propagation solver for SVM : opt_hcy. UCI_iris data sets added.
updated implementation for opt_hcy. In kdtree construction, right child no longer contains the splitting point.
bug fix for opt_hcy
code consolidation for opt_hcy
New algorithm: greedy approximation for large scale SVMs
Stochastic Conditional Gradient Method (scg) added
FW algorithms updated
display testing accuracy
iteration information removed
bias update for nonlinear sgd
display gap on termination
display gap
mimic online senario using random permutation
implementation of Pegasos in opt_sgd.h
infinite max iterations for sgd
1. rename: opt_sga.h -> opt_fw.h
minor modify on shrinking of SMO
minor update on shrinking and n_iter stopping criterion
modify unshrinking
max_n_iter<- 10^8
max_n_iter<-1e8
n_iter->ct_iter in calculating portion of away steps
do w_scale in training session
added L2-SVM using SMO
remove usage of w_scale
separate pegasos from opt-sgd
commit b9eb9359bd02cbf56dfb90e4facdb0c01669c2f5
add no w_scaling option for pegasos
pegasos with bias
commit 95815d6882dd49fa09b5287b96245bf0dcf50944
add n_epochs option for SGD and Pegasos
Coordinate descent for linear SVM; L2-norm regularization option
in online algorithms, permute data set within each epoch
modified epoch scheme
CD working now
DCD sqrt bug fixed
add bias for pegasos
opt-pegasos.h: amortize w-scaling to prediction session
1.move pegasos's w-scaling to training 2. add projection option in pegasos
display projection for pegasos
commit 048c68ca6048c8b4e7c6995f8a401221b62c158b
display gap on termination
add an option to calculate primal objective values
add opt_sgdwb.h
fix bug in sgdwb's prediction
opt_pegasos.h: fix bug in calculating obj values when no scaling
opt_sgdwb: fix bug in calculating obj values
fix bug in do_shrinking
add implementations for LASVM and Robust Ivanov
ID_FREE etc
Now support L1-SVM-C (hinge loss) and L2-SVM-C (squared hinge loss)
1. add SPARSERE solver; 2. regularization_ -> hinge_
normalize=0 by default
%f->%g for coefs
%g->%16g
experiments for SDM
remove msfw, since it's integrated in opt_sfw.h
display portion of away steps
if-> else if
remove redundant init for grad_bar
speed up kernel calculations for NORMA
commit c619b48d4138bbf924360f88ad7c5baebacc7059
commit 5189604f5513a675e05f977039cbf1cbf58e82cf
speedup kernel calc for ct<n_data_ cases
speedup kernel calc for ct>n_data_ case
Initial release of "regularized risk minimization" project
commit 055cf29184a1fbde2a9b4b7e727842e2cf388537
commit b8e832be8cad722c1631f9a0dbfbea5093065411
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commit 2db893ab9e282a61fc96c16983ad1df034476147
commit db9c7fc368849009d1a7a6926c759fdb81487408
Hua Ouyang
commit 15875deb94e71911ad64c60588b970f066c666e2
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commit baf1c7d65cd11ded870e1d596a45f17feee455c5
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commit 39cd2508ab0d4752c9271ead2ee28d0f42bdb007
commit c856f4432cbc24d0308a60fbb21671a77a0ef3be
add dense version for pole
commit 429780dc0e7cacc0e076c1613c49263ed573ba54
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commit 43c8d5c4e73de98c45be89c84e5de3fbead44ccc
commit a7e871126130e4f7b67de7aa6323674f6a1bb5eb
commit 4db38df2275cd1c2f22ea9e6dadadd88e990f815
NASA added.
commit 90d4b33967cbf10e499dddb31d3edc7660badb5d
commit 97475932486749424a37f4ae9b449909b8f0df9f
commit fc58da3380c5225de6a0ecab33370d8cdf45a8bd
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hritik25 (1):
Update TREE_EXPLANATION.txt
jwaters6 (63):
First upload of molecular dynamics code
commit bca971af53850951781e609df78ff56d5e5cd9fc
M md/build.py
commit d9543472bdef9de528836a0b730ce16bb009c8b2
commit 5674d3a1a2bee591c206a436a687fe7c00273a63
modified bounds code to accomodate coordinate offset
commit 388453d9438fa40d4fe77728aea43a43e3034694
commit cd553320249402f307e15f9219658178ce6ebeeb
Revised kdtree & bounds updates to merge changes
Changed kdtree_impl functions to pass by reference (when applicable)
Added periodic max distance
Added CART code from Alex's class Jwaters 11/28/08
commit d6b28167679a2e5e8a5522164335066d45a8faa0
commit aeb44d4565c0ef2e4ca765929072234231df2dfe
M cart/cart_driver.cc
commit c3b33e03c4c96fff9077e798ce5c5de4a5cc7604
commit ac3b1d573e6489a1d54a4e1aab0308e1c1049a78
commit cc6bba4857088cb6e9cb2ac827b943a78e8e0588
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commit 808cb6e084542b4411aa820fc6193a9b0bcd5e0c
commit 1814d829f012a91afc271e010804ef7f6dee263c
Added MD code to fastlib2 repository
commit 553e5b53fe80b3bb781bc2d1c9214194e29c58ea
commit c8233ec49dff0c3c86f0b2015291a10ce905b519
commit d00281f5b51acf5972456abd2271f43d9217d333
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commit 6e925a2aefdbc0f3d7cfd5f35037af60fa2a71dc
commit c52383ff6d56424bed205998d620fb632e16fcc5
commit 843d1050bf98a3df4a4c03f508b9e88952924598
commit 4cad44539766aff308d0e79b20be9d88a9a27783
commit ba9a8695631219e64e6a939ad320562566bb4a00
commit 2b83fa37017041b037fc7234e64d19dabd29006d
commit c829f7b8995c0e3a0802b3103821a9be24d33282
Modified multi_physics_system.h to
commit 1601d63456a316247dc561730dc4001ff4065f03
first commit of thor_md for parallel molecular dynamics
commit bf29a8f074ca7dc2448ac0afb29bf71412a6041a
commit ff3dcb40e71fba7dd8555c7509f65e3cc64c8ff9
commit f130231108349b115738f2875e16c436f3543e8f
commit e5c738fb2e426832e2e98e8751cea92013ab430b
commit d353a7ca1d4a6b081cae136739f9a33fb003de26
commit 06475daf142052bce032ee8f49d5146e1255454c
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commit 4a997e9441cc1bdcaa95003359b7781225bd046a
leif (31):
Initial upload of the open-source CMakeified fastlib
Oops. Wrong version.
Correct version of OS, CMake-ified fastlib this time, I promise.
Add branches subdir
Add tags subdir
Identified bug when reading Mac files (eol = '\r')
Added Mac eol bug to docs to warn people direly.
Removed manual flag-setting that was messing up CMake automagic build_types.
Optimization half-working
added note to narrow native fastlib optimizers' deps
fixed typo in opt++, removed test code unwittingly checked in.
Moved optpp to opt++
In a bold move, removed the README instructions for fl-build.
Fixed optimization dependencies broken by moving files.
Fixed some broken dependencies caused by moving around optimization code.
Added an example to demonstrate compiling & linking with OPT++.
Updated README to include info about OPT++.
Removed noise from toplevel cmake file.
Linking failed if opt++ was installed someplace nonstandard--fixed.
Added directions on where to download opt++.
remove annoying file
remove annoying file
started changing copyright info
Fixing copyrights.
Fixing copyrights -- done.
Generated fastlib includes shouldn't be in svn.
added trilinos libs to cmake link libs
starting to update to trilinos 10.0; disabled a #define that mangled code,
fixed many of the easy typos, most having to do with templates
Added sparse matrix code to fastlib, added Trilinos instructions to README.
Tiny change to fix link errors when building fastlib as a shared lib.
marcus (23):
Add a test for AdaDelta.
Add a test for ADAM.
Widen tolerance slightly and disable non-deterministic behavior by setting the shuffle parameter to false.
Add convenience typedefs (ReLULayer, TanHLayer).
Add tests for the current init rules.
Minor formatting change.
Use the new optimizer interface.
Refactor recurrent network main class for new network API.
Add SFINAE pattern for the RecurrentParameter function.
Add SFINAE pattern for the SeqLen function.
Set the sequence length if necessary.
Reset the recurrent delta at the beginning of a new sequence.
Refactor LSTM layer for new network API.
Use the correct number of parameters for the LSTM LayerTraits.
We can't initialize a matrix with an uninitialized matrix.
Add recurrent layer.
Minor style and formatting changes.
Refactor recurrent network test for new network API.
Minor style and formatting changes.
Fix the include guards to avoid the problem ofdouble inclusion.
Slightly increased number of training epochs in the SequenceClassificationTest.
Build the recurrent neural network code.
No need to reset the scale parameter in the forward pass of the dropout layer.
marshall (22):
included "assert.h" in fastlib/base/common.h
removed periodic distance funcs from bounds.h, and moved to periodic_tree.h in my own
commit 0dbb00491be347bd42ab2ad8c0f9461445f95eac
added synchornization calls to thor_md.h
commit c83602463431e874ef7b4f2e9139ceb51db57091
commit f10639134debf8afb0e28b58f8b83d4c9eccf622
commit 4d0c8780c8f91d3340ad40c776c97cb63295de19
commit a95929744501addce86a66ac09703cdaacd1dcff
commit 3126c5dfd558b987c7f136d8c3c7e468220a8ff0
commit 285eb1ebff34524386d0cd3ff6538a6f6260d750
commit 15e2259c24ad66149f2e3216a155229ba5173418
commit 6018c336765aa792c8d52b34ff91175617e849e5
commit cc5f5f54950bdc8a3818421e24eff7a526244615
Added Inlcusion pruning in Cartesian case
commit 76b474e1aea8cf1eef6233da2c9f4c0f6758ea30
commit 214d2cc588cda99e8371d10ad5007eea8df5f20b
commit 70251015fd6feca0b8b46452d713c48e9a25aa3d
Inclusion pruning for 2pt, corrected
Corrected inclusion pruning
commit d4a93bef2bdf4f3c13311b58a2599d783aa6915f
Weighted 2-point correlation
commit 0bdf56485426a27321e20be3ebd9a20c7bc3ca05
michaelfox99 (50):
fixed ticket #316 (hmm::Predict() in hmm_impl.hpp)
fix forHMMTest/SimpleDiscreteHMMTestViterbi
Removed phi, added gmm_convert_main.cpp
Removed phi, added gmm_convert_main.cpp
Changes to work with new, hierarchical GMMs
Changes to work with new, hierarchical GMMs
utility for converting legacy GMM XML files to new format
Hierarchical GMMs store params in GaussianDistributions. Makes code clearer and simplifies Save/Load.
Changes to work with new, hierarchical GMMsHierarchical GMMs store params in GaussianDistributions. Makes code clearer and simplifies Save/Load.
Hierarchical model support
Hierarchical model support
Hierarchical model support
Hierarchical model support
Hierarchical model support
Implemented Save, Load
Implemented Save, Load
Implemented Save, Load
Implemented Save, Load
Added hmm_convert (legacy file converter util)
Hierchical model support
Implemented Save, Load for hierarchical model support
Implemented Save, Load for hierarchical model support
Added legacy file conversion
Legacy file conversion, deprecated old SaveHMM, LoadHMM functions
Legacy file converter util
Added Save, Load tests
Updated Save, Load tests and updated tests for hierarchical format
GMM::Save() now adds type information to XML files
phi.hpp no longer used, see GaussianDistribution::Probability()
removed #include <mlpack/methods/gmm/phi.hpp> which included only unused functions
added Save(), Load(), Type() to LaplaceDistribution
intercept no longer penalized and can be turned off, observation weights now supported
intercept no longer penalized and can be turned off, observation weighs supported
typo in comments
New distribution (a combination of LinearRegression and GaussianDistribution) for implementing HMM Regression.
Implementation of HMM Regression
Added HMM Regression files
Added Smooth and Filter functions
Added Smooth and Filter functions
Added regression_distribution.hpp/cpp, removed hmm_regression
Rename hmm_regression.hpp
rename hmm_regression.cpp
now regression_distribuiton.hpp
Now regression_distribution.cpp
transition now protected, not private
HMM regression method
Implementation of HMMRegression class
hmm_regression.hpp and hmm_regression_impl.hpp added
Dimensionality() now returns proper values
Re-ordered initializer lists to fix warnings
mohanrajendran (10):
Added a compilable version of NMF code. Test cases need to be written
Basic implementation of NMF
Add nmf directory
Move everything into the NMF directory from PCA
Move NMF out of PCA
Revert to PCA CMake configuration
Unit test for NMF added successfully. Validation conditions need to be tuned
Added Aleternating Least Square method to NMF. Require some testing
Wrote all the NMF test case and updated Alternating Least Squares method with pseudo-inverse function'
Fixed NMF Test
mudit3774 (6):
CF framework and ALS added
Adding Cosine Trees
Added tests for CosineTree and CosineTreeBuilder
Added tests for CF Module
Converting row-major to column major
Removed an older version of tree test and added a new one
nadeem (12):
Adding beginning stub code for parallel EM
Very early draft of a document that should eventually become the FASTlib Manual.
Updated documentation
updated directory structure
A brand new repository with the new directory structure.
removed a useless file
commit f4a7dfa773162c0547ca8635bcc4c4bb44789227
A brand new repository for the new directory structure.
commit e2d6f7a3a5fdacb4bab983ab01e5b26485803a4d
commit 3357ce9c91e87646a36b9ec11afbe65ce36b8ad7
commit c09df3247f8a1425956a42f091504f174d48c0dc
moved from the old fastlib repository
nkauffman3 (48):
Add io.h to default include
commit 8b2b64e298200416b1ae0fcf6a1daf3418b6ee3e
--Converting fx-style output to IO output
commit ae35b9b0725f5d27d36dc70e3abf04ada949fbda
--Convert FX Style Output to IO Output
commit b38999bf1bc3f5703bc171ec6ad52730e5387eae
--Convert FX Style Output to IO Output
commit af3a50e87aedf3521d9c8c668b9217a7a0d59e47
--Trivial Remove Copyright Notices - ticket 84
--Ticket 85 -- Convert tests to Boost Unit Test Framework
-- convert to boost unit test
-- convert to boost framework
-- Convert to Boost Unit Test Framework
-- undo changes from last build
--Conversion to Boost Unit Test Framework
-- Try to unbreak build
-- FX Conversion to Boost Unit Test
--Conversion to Boost Unit Test
-- Convert to Boost Unit Test FrameWork
-- Convert to Boost Unit Test Framework
--Convert to Boost Unit Test Framework, Still Needs Macros Removed
-- Conversion to Boost Unit Test
-- Convert to Boost Unit Test Framework -- this might break build
-- Convert to Boost Unit Test Framework - Ticket 85
-- Convert to Boost Unit Test - Ticket 85
-- Convert to Boost Test Framework - Ticket 85
--Convert to Boost Unit Test Framework -- Ticket 85
--Convert to Boost Unit Test Framework
--Able to build, but running test case throws : run-time error: qr(): need LAPACK -- on my machine. Want to see if this fixes build (meaning i need to update lapack)
-- Undo infomax changes --- will redo tomorrow
--Undo changes for kernel pca -- will fix tomorrow
-- undo ridge regression changes -- will fix tomorrow
--Convert to Boost Unit Test Framework, Ticket 85
--Convert to Boost Unit Test Framework -- Ticket 85
--Convert to Boost Unit Test Framework
-- Convert to boost unit test framework
--Convert to Boost Unit Test Framework -- Ticket 85
--Convert to Boost Unit Framework - Ticket 85. Code is causing issue with new test cases that do not use pointers.
--Convert to Boost unit Test Framework -- Ticket 85 - will remove test_infomax_ica.h in a sec
--FX Convert to Boost Framework - Ticket 85
--Convert to boost unit test framework - ticket 85
--convert to boost unit test framework -- ticket 85
--convert to boost unit test - ticket 85
--convert to boost unit test -- ticket 85
--convert to boost unit test framework -- ticket 85
--Convert to Boost Unit Test Framework - Ticket 85
--Convert to boost unit test framework, ticket 85; replace reserve with resize()
--Convert to Boost Unit Test Framework, Ticket 85
nslagle (51):
branches/fastlib-stl: fix #63; remove several warnings
branches/fastlib-stl: undo the insertion of Wall until I can address the additional warnings
branches: fastlib-stl: fix #70 (for now, with hopefully minimal damage...)
branches: fastlib-stl: commit a few space changes and function replacements
branches: fastlib-stl: attempt to fix #72
branches: fastlib-stl: remove some unnecessary whitespace
branches: fastlib-stl: eliminate a few new warnings
branches: fastlib-stl: remove Dataset and Matrix dependencies in nnsvm
branches: fastlib-stl: mlpack: nnsvm: reorganize the code slightly
branches: fastlib-stl: mlpack: nnsvm: adjust some spacing
branches: fastlib-stl: remove a couple new warnings
branches: fastlib-stl: mlpack: nnsvm: add initial testing support
branches: fastlib-stl: nnsvm: commit the latest changes for RC to examine
branches: fastlib-stl: hide code that generates warnings
branches: fastlib-stl: remove a couple constructor related warnings
branches/fastlib-stl/mlpack: remove the Dataset dependency from svm; modify some formatting in nnsvm
branches/fastlib-stl: shamelessly hide the broken tests for now
branches/fastlib-stl: remove a few warnings
mlpack/trunk: modify the clamp function
mlpack/trunk: modify the clamp function
mlpack/trunk: fix the ClampRange mistake; the previous functions need more intuitive names
mlpack/trunk: delete an extra space
mlpack/trunk: per bug 131, add a SaveRestoreModel (and abstract Model) class(es)
mlpack/trunk: eliminate the newer call to clear breaking the build
mlpack/trunk/src/contrib: create my directory
mlpack/trunk/src/contrib/nslagle: copy the kde code base from D Lee
mlpack/trunk/src/contrib/nslagle: continue updating kde
mlpack/trunk/src/contrib: revert changes to the CMakeLists.txt
mlpack/trunk/src/core/tree: revert the statistic.h for now
mlpack/trunk/src/contrib/nslagle: commit fledgling kde kcde
mlpack/trunk/src/contrib: hide PRam directory until the missing file reappears
mlpack/trunk/src/contrib/nslagle: add and modify more of the KDE code by DL
mlpack/trunk/src/contrib/nslagle: remove my directory from compilation and testing (damn you Jenkins)
mlpack/trunk/src/mlpack: rearrange and restructure the save/restore mechanism; clean up some code
mlpack/src/mlpack/core: remove files I accidentally re-added
mlpack/src/contrib/nslagle: continue modifying the KDE code
contrib/nslagle: newest, not yet working KDE code; multi-bandwidth, dual-tree
mlpack/contrib/nslagle: add the multi-tree base function
mlpack/contrib/nslagle: add the multi-dualtree function
mlpack/contrib/nslagle: commit more changes
mlpack/contrib/nslagle: commit a possibly working version
mlpack/contrib/nslagle: correct for bounds; track the success level for each bandwidth
mlpack/contrib/nslagle: commit more tweaks
mlpack/contrib/nslagle: commit the latest changes; the binary tree apparently is not full
mlpack/contrib/nslagle: I wonder if the algorithm ever really worked...
mlpack/contrib/nslagle: the algorithm almost works...
mlpack/contrib/nslagle: KDE almost works, again...
mlpack/core: apply some changes to HRect, Log, and BinarySpaceTree
mlpack/core: undo an unnecessary change; remove a pesky warning
mlpack/core: add std::vector as a save/load valid type (so long as the templated type is basic, for now)
mlpack/core/kernels: add a couple of kernels appropriate for the forthcoming KCDE/KDE combo, per #200
pagarwal (8):
start building wrappers for Numerical Recipes
moving the directory
adding directory of numerical recipes' code
test file for numerical recipes.
added 'pagarwal' directory.
developing optimizer wrappers from Numerical Recipes.
test if NR is working and start quasinewton optimizer
Take out Numerical Recipes from the repository and save the lab from potential license violations! :)
pmason8 (4):
commit dfa9fddf07781e1160f27cf193f27950aa46245a
added range_search and gmm; CMake updates for kmeans
lars, nca, nmf, pca, kernel_pca
cleaned up commented code in allknn allkfn. adding the incomplete hmm binding
rriegel (135):
commit bd7b5d66bd375cba96141d02664da5a36c64eb4f
finished GNP section
finished GNP section
section 4 added
proof of all-nn
all-nn and nbc proofs
proofs, theorm format
docked intro
starting affinity revision
starting affinity revision
further affinity
further affinity
most of affinity
cutting nbc
affinity damping
mention of trees
mention of trees
mention of trees
mention of trees
pictures, bib
intro
reverted
working on GNA
working on 2pt
working on 2pt
working on 2pt
working on allnn
refreshing proofs
refreshing proofs
refreshing proofs
refreshing proofs
refreshing proofs
some revs regarding reviews
initial nbc: upto Algorithm
first pass nbc
nbc compiles
first stab at bichromatic/LOO
numerical problem fix: clamp positive
some problem with too small ubs
bug fixed; appears operational
something wrong with not labeling stuff, maybe
fixed commutative -> reflexive for distance metric def
fixed e.g. -> i.e. (my bad)
final?
final
siam added
single and multi versions
nbc changes to THOR - breaks things
major overhaul of base directory
minor style changes in base
removed cursed using namespace std
forgot base.h
reverted changes to success_t
DEBUG_SAME_INT -> DEBUG_SAME_SIZE
removed a few Makefiles
guide added
minor changes to base
allnn_main.cc documented
allnn.h minor module fix
platonic allnn complete
correction to ot::print comment
added Init checks; bug fix
OT_DEF comment, removed dumb DEBUG test
fx_get_result functions
mem past-tense names now present
formatting, dos2unix
looser mem::BitCopy typing
fixed dir example -> wwong
svm appears to have moved to u/houyang
fixed build.py deplibs
added deprecated includes
restored example
sed tabs to spaces
fixed Nick's weird tabbing
exclude trilinos in Doxygen
DEBUG_SAME_DBL -> DEBUG_SAME_DOUBLE
removed compiled manual
revised introduction
final draft
more revision
copying revised, formatting
THOR updated
documentation for fx modules
fixed unit tests include
removed Makefile; limits.h; ccmem out-of-memory messages
LOO by index, not dist
fixed non-BLAS LengthEuclidean
some memory optimizations
templatized matrices
fixed test suite, fixed arraylist ambiguity
beta revised ot, ArrayList
rectified missing ccmem.cc
added deprecated debug macros
removed loads of test results
major fx update
general overhaul for fx update
added kda
store -> output for compatibility
better matching by --help
todo at top of allnn.h
fixed Copy -> InitCopy change
Simulated kdB-trees in THOR experiment
fixed fx silliness
fixed config.py header
spelling
single tree support
single tree modification
bad percent sign
comment typos corrected
ENABLE_DISK_MATRIX option, default off; fixes to fx includes, uselapack index_t usage
parameter type fixes
fixed cflags for basic_types
advanced to new fx
changed ENABLE_DISK_MATRIX to DISABLE_DISK_MATRIX
DEBUG_DESTRUCT_OK added; DEBUG_ONLY enhanced
fixed thread.h DEBUG_ONLYs and kde's VERBOSE_MSGs
fixed QRInit test for new LAPACK
revert to best working THOR
reverted to old, better working THOR
revised nbc for demo
Rejoice! --fx/no_docs_nagging now available
Dataset no longer compiles with warnings in gcc4, THOR no longer uses deprecated functions
fixed some accuracy reporting bugs in q \neq r case
fixed emst clust
preliminary NBC commands
fixed gcc4 not found issue
and fixed fl-build-all
fixed checking for gcc4
fixed fx/no_output_types name disagreement
added query point ref node prune
fixed potentially bad printf
fixed a much outdated Copy -> InitCopy
fread/fwrite retval checking
removed added links and fixed #define LT -> LTSC for OPT++
removed fl-build's use of j except when specified; corrected some #include's to use explicit paths; other minor fixes to mvu and lbfgs
ryan (305):
Tabs to spaces (trivial commit; testing gitdub email notifier).
Minor tabbing fix; still testing gitdub.
A (potential failure of an) attempt to use alternate headings to make things easier to read as flat text, and also to use relative anchor links, and also to convert 'MLPACK' to 'mlpack' for consistency.
Conjugatin' da verbs.
Add download link, for people who come across mlpack via Github but might be better served by a stable version.
I meant for this to be bold, and vim even told me it wasn't going to be, but typical me, I did not listen.
Minor change to test gitdub.
Clarify the warning.
Merge branch 'master' of https://github.com/mlpack/mlpack
Slight style changes, and comment utility functions and put them inside the relevant namespace.
Simple change to test Jenkins webhook.
Change build status URL.
Minor syntax change for Jenkins repo testing.
Simple spacing fix.
Add .gitignore file for build directories.
Add new contributor.
Trivial capitalization fixes for style guidelines.
Modify tolerances for NMF tests.
Loosen default tolerance: accelerate convergence.
Remove some RandomSeed calls for reproducibility.
Minor capitalization fix for consistency.
Minor style fixes.
Use accu(a % b) not trace(a * b).
Change trace(a * b) to accu(a % b).
Ensmallen dataset; test speedup about 25x.
Slight refactoring of dual-tree k-means rules.
Beginning to refactor dual-tree k-means. So far the Pelleg-Moore rule is properly refactored (well, sort of, at least). Try to move IterationUpdate() into DualTreeKMeans::TreeUpdate(); for now this will make the algorithm simpler: instead of updating on the fly, update after an iteration. It may make more sense to do updates on demand later, but let's make the algorithm work first...
Add new(ish) executables to 'make man' target.
Don't forget the perceptron.
Refactor CoverTree to allow sparse datasets.
Put the documentation in a more relevant place.
When compiling, see if ARMA_64BIT_WORD is enabled.
Check arma_config.hpp when compiling with mlpack.
Ignore auto-generated files,
Make sure we use the complete type.
Use complete type, which simplifies code too.
Take different types for each kernel and metric argument.
Don't overwrite arma_config.hpp unless needed.
Allow Centroid() with sparse vectors.
Make sure traits are active for all cover trees.
Refactor FastMKS to allow sparse datasets.
Add a test for sparse FastMKS.
Remove unnecessary splitDimension and maxLeafSize.
Fix change I left in that I meant to take out.
Don't call exit(1); throw an exception.
Make Assert() throw an exception too.
Update documentation for functionality change.
Update output for Log::Fatal crash.
Add wrapper for boost::serialization.
Update documentation: program no longer exits.
Add list of formats we can load.
Update CMakeLists.txt.
Convenience function for extracting extensions.
Add Load() and Save() for models.
Move serialization shim to data/.
Fix syntax and include errors.
Add boost::serialization to dependencies.
A few first tests for serialization.
Add serialization for arma::mat.
Add serialization for sparse matrices.
Refactor includes to include serialization code.
Add Serialize() to distributions.
Add tests for distribution Serialize().
Add Serialize() to kernels; not yet tested.
Allow serialization of linear regression.
Add shims for arrays.
Fix typo.
Comment out unused member.
Fix memory misuse.
Add shims for pointers.
Update comment for serialize() interception.
Add Serialize() for empty class.
Be safer with memory usage.
Add Serialize() for HRectBound<>.
Add some more tests.
Update documentation.
This constructor doesn't take a set.
Remove unused class member.
Fix bug where query set gets modified.
Add sameSet parameter.
Refactor NeighborSearch like RangeSearch.
Refactor for new NeighborSearch API.
Fix traits, other slight bugs.
Refactor tests for NeighborSearch API.
Document API change.
Refactor executables for new NeighborSearch API.
A first pass at refactoring BinarySpaceTree.
Refactor tree test.
Merge branch 'master' into serialize
Refactor NeighborSearch internals to deal with the tree holding the dataset internally.
Refactor tests to deal with modified NeighborSearch.
Document when singleMode is useful and add SingleMode().
Refactor FastMKS to take individual queries in Search().
Tiny spelling fix.
Refactor RASearch to take queries in Search().
Refactor test.
Update history.
Merge branch 'master' into serialize
Fix glaringly obvious memory leaks.
Fix #406.
Add serialization for statistic.
Fix memory leak when overwriting bounds.
Add BinarySpaceTree::Serialize() and tests.
Fix some style.
Remove unnecessary LastDistanceNode().
Add Serialize(); remove unnecessary LastDistanceNode().
Provide per-iteration information; avoid W*H.
Add sanity check for #428.
Fix typo that caused rank to be 0 by default.
Allow the Intel compiler too... not that it works.
Allow calculation of RMSE.
Old Armadillo versions needed a second parameter for norm, it seems.
Refactor to match TreeType API.
Add typedefs for common tree types.
Refactor to take a MetricType.
Make Power and TakeRoot available for other classes.
Refactor to handle new HRectBound API.
Further fixes for new TreeType API.
Refactor DTB to use new TreeType API.
Specify metric:: namespace.
Specify metric:: namespace.
Refactor for new TreeType API.
Refactor FastMKS to new TreeType API.
Refactor NeighborSearch to new TreeType API.
Refactor CoverTree to new TreeType API.
Minor refactorings and fixes.
Include template typedefs.
Add default template arguments.
Update documentation.
Update documentation.
Missed a function for the changed HRectBound API.
Refactor for new TreeType API.
Refactor for new TreeType API.
Refactor for new TreeType API.
Refactor for new TreeType API.
Refactor all tests for new TreeType API.
Add convenience template typedefs.
Refactor utility functionality into RAUtil class.
Refactor to handle interally-copying trees correctly.
Refactor test to handle internally-copying trees correctly.
Refactor for non-modifying TreeTypes.
Refactor for non-modifying TreeTypes.
Document the KernelTraits struct.
Fix two FastMKS bugs.
Allow .tsv extension too.
Update documentation.
Add DatasetInfo class for categorical features.
Add tests for DatasetInfo.
Rename to match other enums.
Stub of new Load().
Count lines by hand; and trim whitespace from tokens.
Flesh out tests for DatasetInfo Load() functions.
Rename .txt to .csvs where necessary.
A first pass at the abstractions for VFDT.
Add a basic comment.
Finish Range test.
Fix compilation warnings.
Remove debugging output.
Fix epsilon calculation.
Add some more tests for HoeffdingSplit.
Get HoeffdingSplit and StreamingDecisionTree to compile.
Add numeric split info.
Fix test number of classes.
Add test: equally good features should not split.
Implement numeric feature support (though stupidly).
A more complex test for HoeffdingNumericSplit.
Fix build warnings.
Set initial parameters correctly; restore tolerances.
Add another test for the numeric feature splitting.
Add a command-line program for streaming decision trees.
Handle numeric and categorical attributes simultaneously.
Force splitting after enough samples.
Fix ambiguities and use of at().
Fix serialization bug.
Fix compilation issue.
Serialization support.
Add serialization prerequisites.
Add Serialize().
Test HoeffdingNumericSplit<>::Serialize().
Add test for HoeffdingCategoricalSplit.
Fix (kind of) serialization for HoeffdingSplit.
Fix a really, really stupid bug.
Hold a pointer to the dataset info, and serialize accordingly.
Allow serialization of dataset information.
Serialize correctly.
Don't overwrite majorityClass.
Save the tree.
Test StreamingDecisionTree::Serialize().
Add a way to get the probability at each node.
Revert unintentional commit.
Fix -Wuninitialized.
Add convenience typedef.
Make sure memory is initialized before loading/saving.
Better main executable.
Fix compilation errors; add a first test.
Add better test; fix bug.
Add NumChildren() to use instead of Bins().
Add test for binary numeric split.
Remove debugging output.
Use easier-to-understand isnan().
Check isinf() too.
For monochromatic dual-tree search, the bounds may need to be reset.
Add a test to ensure that doing monochromatic dual-tree search resets bounds.
Handle when we have both categorical and numeric features.
Add a primitive ARFF reader.
Add a test for the ARFF reader.
Add another test.
Test Classify().
Fix bug that could cause a hang.
Don't issue a warning for one-column CSVs.
Use a pointer to the dataset.
Add Serialization() to NaiveBayesClassifier.
Fix collision of variable names.
Do unmapping correctly.
Test RSModel.
Be more clear with the warning.
Refactor range search program. Allow model saving/loading.
Force settings of --single and --naive.
Refactor to allow passing parameters of splits to children.
Allow specification of the number of bins and observations before binning.
Remove ToString() from everything.
Update HISTORY.md.
Remove special handling for ToString().
Rename Regress() to Train(), and allow retraining.
Update API, and add tests for retraining.
Update for API change.
Add Serialize() and a test.
Refactor executable to allow saving/loading models.
Refactor constructors; rename Encode() to Train().
This is a more correct implementation.
Fix bug in test by initializing leafSize.
Merge branch 'master' of https://github.com/mlpack/mlpack
Refactor main program.
Add newline after message output.
Install the hoeffding_tree program.
Refactor nbc program to allow loading/saving models.
Don't print "Required options:" unless we need to.
Standardize options.
Better documentation of save failures.
Better program documentation.
Refactor main det program.
Better documentation.
Only use template parameter for training.
Add default template parameters for Train() overloads.
Add tests for Train().
Add tests for Train() overloads and empty constructor.
Remove unused rating matrix.
Update documentation.
Add Serialize() implementation.
Add serialization test.
Fix dependencies.
Refactor main CF program to allow loading/saving of models.
Don't use a reference internally.
Add empty constructor and test.
Add Train() and tests.
Update documentation.
Fix memory leak.
Remove unused amf program.
const Serialize() functions don't get picked up right by the compiler.
A better memory leak fix.
Add Serialize() and tests.
Allow access to naive.
Add Train() with a tree.
Add a model for FastMKS, to be used by the command-line program for serialization.
Add tests for FastMKSModel.
Fix -Wunused.
Add tests for FastMKSModel.
Refactor main executable.
Fix bugs; add KernelType().
Fix #229.
Update tutorials.
Properly list all available algorithms.
Merge branch 'master' into vfdt
Use mlpack_ prefix.
Add mlpack_hoeffding_tree to list of targets.
Add PROGRAM_INFO() documentation.
Update HISTORY.md.
Outline the versioning policy. (This can change, of course, but I think this is a good start.)
Bump version; everything from here is 2.x.x or higher.
Fix dependency documentation.
Fix build bug.
Standardize: 'mlpack' instead of 'MLPACK'.
Use .csv extensions not .txt extensions.
Fix test condition.
Wait for long tests with no output.
Test with arma::chol() not arma::det().
Loosen bound since it is probabilistic and we have many tests.
Initialize dsPrediction to fix failing test and uninitialized memory.
Further loosening of tolerances to increase probability of success.
Fix test filenames.
Loosen test tolerance slightly.
Make Newton tolerance larger so the method actually converges most of the time...
Ensure a larger set of original singular values.
Fix -Wmaybe-uninitialized.
Due to technicalities, the tree we load back may not be exactly the same.
Update required dependency versions.
Add headers for files missing headers.
Add header.
Add license information.
Add date of release.
Remove unreleased features.
Update version numbers.
Compile without debugging symbols.
Remove ANN tests.
Remove build artifacts / git artifacts.
sooraj (90):
Initial import
Removed .mlpack files, which can be auto-generated by bin/mlpack
Fixed a typo in the comments
renamed module Syntax to Ast & updated test.ml to reflect this
update mlpack script to ignore .svn dirs
minor revisions to AST
commit baa29d45ef84223500c92022cada0ae956a2bea7
commit 92b4a2cd0378ced259fa4b255c36681227a55cc2
added freeVars stuff
commented out portions of interfaces, updated _tags
commit 07cfba6ad2d33bdfffeebbd15c160451d75f0019
commit db297fec3578af3636c702fee210d8bfdd21acb1
simplified everything to more closely match the thesis
commit db8f0db1f611afe604557760c0c2e20ffdf2799d
final simplification pass
commit 3fa2dd0279b363b6fea297f468c2f5bf1619f301
commit 13c40bec17d922d1800b9826fdc41597ce722097
added CNF stuff
refactored and cleaned up a bit
toying with interval stuff...
added the first of compilation transformations
commit 621aeb9eea32f4f5bc835b955afe4e4e8b5719b1
added almost all compiler transforms; added an EDSL
in progress changes...
all done except compiling disjunctive propositions
commit 3ef29b017bb563d2f34788d8e31e1989d55e2571
started on pretty printing
commit ee0c16258d90420ad3f553ef40b17bd16d97823c
commit 5814b0bcf28880cf3cfb0176f8203794bb5321d4
moved files to 'mp'
commit 2375168d014807f30a311835a338da1c2313b79d
finished moving stuff around; everything builds
fixed _tags to be less promiscuous
commit 470fd776eebd26fe6a39dcc3b781e80f710adcad
added examples
fixed a bug in isProp
started on the disjuction compiler
commit 86021f88c4070d8ea9055a7976e7af01b4fa8839
finished chapters 4 & 5!
fixed minor big in scalee
added a disjunctive example
initial checkin of RV writeup
commit b03f5c8a36e03c1fd6e7bc439099e29d930b1b4f
commit 23b64b809e91400c4232f2d3c250e82a863dd5d4
added conversion to prenex normal form
commit e8a7a311c5e13ba90f38dd509278c72b5a943805
added some utilities
commit 0c8acaea1a7c07d11c4a29578f47e778bdc2ab75
added smallcheck
commit dc5ef9e87e1db8f9d35422f5a0db1a71f21eed7c
first sane version of smallcheck!
removed redundant function def
moved Show stuff to one place
commit 9ddb3a7c77db07b3ee44c1066e5c3e4c76ec2433
refactoring some printing routines
renamed pretty printing functions to be more accurate
stable build with a more sensible dir layout
commit a9e4aafb105c01a07cb66e57e1f92dd31f08d673
commit 8f6ce0dd08b821d087eeab1e529a6c66f58b2539
removed [the beginnings of] difference lists...decided not to use them
fixed the build :o)
commit 1d79fa5a2eb3a717715ce6a476230b89649a0004
added a functioning SmallCheck.forAll
commit c19805b0dd81d3258e0d8e3490865f459d33f85f
new import
new import
fixing botched tylesBase import
fixing botched tylesBase import
fixing botched tylesBase import
commit fbb586fefcd4d61188e006a4d28bc72473bd234d
switched away from -pack and towards my new idea for hierarchical moduling
commit f0fedf1a684e7a5f97e1990aa972fa50b49cb8d3
switched SmallCheck to a new representation
merged conflicts
started on Big-M compiler
renamed 'mp' to 'mathProg'
fixed build errors
moved 'pprint' to 'pPrint' for cosmetic reasons
moved utilities from mathProg to tylesBase; will refactor further
commit 48137e11261b5f813c622a6940580153e4b78b3e
moved utilities from mathProg to tylesBase
commit 897a1cc90bb346b09fd046c6bc4db3e70a71c26e
commit 173d2246597de0576ac5974bab263c858a07e386
commit 327fdd5a4121a72fbfa53a2e507b263abd875e33
cleaned up everything to use TylesBase
removed util.ml
commit 932f80828af3d17d63e6e7310e0365f92e726b46
commit a19650e504084e10444efe461d6eb01ffa47327f
fixed a pattern-match warning in smallCheck.ml
added Option.map2
soyeon (172):
Made it to run on cygwin yeeeee
I added Soyeon as a user
Added the LINE_MAX macro so that it works with CYGWIN
Nick introduces sophia in the world of CS wisdom
Added the build file that I had forgotter
Added a more advanced result
update
update2
It compiled
review&add comments
10-29 in progress
update
Our first attempt to hit the problem
commit a23d6c923f7ef8cf9df4ac104291434fbf5f0a17
objective function calculation
commit 5cb390e7169a5499c84d96b9ddefc6db7a1c16bc
objective2 is added
updated
update
update
update
until 1st&2nd derivatives w.r.t beta
updated
until w.r.t. beta, p, and q
until w.r.t. beta, p, and q
until w.r.t. beta, p, q, pbeta, qbeta, pq
sampling
commit 0de957af5801ff9a7915af80106f046f564cf0e9
update
update
update
Beforre nick leaving
ready to debug for the calculation of objective fn
it compiles
error
commit d303e1c909b00f405347a2fe902c63c303ce4179
commit 3c8e60060e8719318939434e1ae3366db242a027
commit 9107af7c6c3208feab201de0f9e627ac9aa13571
done with debugging until objective fn calculation
commit 686ff00841ad84bd43258cf85b4765b5fead20b4
commit 73d9a75a9fb6a2ef5fccdcb9296ac17cb5e7242e
error correction
compile
commit c484aa0b6c2be9a62c7ac7d9f31b6c171fae472a
commit 7d2c981f1e721acd8db16d9a98874de642a13cf8
commit 4af13e79fa411f081c0fb62b3368995697a4aeb1
commit fa031e9bb4b5bd04c6e81a9537347272fc8eeb8a
commit d835be499f331b326dc12c891b978ae8cdd0b9d6
commit 00224372f039d98fe6fdbea3852e8c82a61c1aa1
objective fn and gradient vector Done
Completed objective fn, gradient, and hessian calculation
commit dce0acf79faa8924c1f234c2f59aee69e46f55f1
commit f53edc52444a70a28c55f474dd5ca413c9eeb31c
commit 0fb0c40f864ab5103e984e4c8d4dd8853319b9e5
commit ee9848b14e3c48f3c30090b3238b3bd0dc67d757
commit f653688093bf390bd4141d6c5dc1a2d7e32fea25
sampling compiles
commit e1d975a9d64fd4f6919d28927ebde93cc622f39d
commit f60ba2cbaee1f8393bdd4e6fa7aba667b3cb80dc
sampling works
commit d90207578dcf26d942878fb9a522438d9a7a5624
commit 54861cb1f973aba9eb10948c772b1c30de313cf5
commit 460792ececd733a62e022748aec04047ceb1b61f
dogleg
dogleg works
Steihaug works
commit 128165463135d83e40d1b0aef43907a143e598af
commit b9136cfdd857eab598886a853992c1beb30e05d6
commit cac39504818f8ef693f28bfa1b91e5e3366dfcdc
commit b23b388576c5419211e77db9020ea731e2e3bee9
it works
commit 6e47b28dc0d9bedbc17d54657f8fd5e25e252272
commit 727e3fb127138614ed443630c06572426f709f98
commit a8b5b92aac21acacd247ae3b3a95a8dd758c2a4f
commit 96a01094ef705a8b23f874dfe43d017982fd7d7e
commit bf9906a194fd7015110c764aca405971bdb71a99
commit 97c7a0d0f426c76c0f1092943efec0a3391f7ce0
commit 61004afce88e45f1267702a68bd50aaceb3ef357
commit 6e177ab8a74d92a0ebc5ac4571c609c842e4efde
commit 17777fbf79888f42adff387ea241ade03d6d5efb
commit ba75f060010132fa3817fed1a7f96207cb75fb98
commit 9a883a25b0eabfef6e59b9ca264fa92f53e160fb
It is working
commit 6ecd2d1840cdd1a63a20099a25d1408956fe5609
commit 22303c2a19ed1367d31904d7db84f05f6088addc
commit e59c0497fc88e2b5896f517c86701ef843b376ff
commit fee606d334c0cf197dd053f567cc68e7bb2579fb
commit bc8465e05d16e30f56896fdbbeedec5647036590
commit 32ce2f2728c355c9d965e2211a08025228db2623
correct hessian
before scaling
correct one error first_stage_y[n]-1
trust test
commit 05ee6a875a9cd787c37908db38a0f0e5ef019b70
commit e4f40333e208ad0ccf495d9075aa3ce836717b08
commit 7d2e45f4d76b188bd37f06e9933f6b76f95f34ab
commit de910cb8d36e15e40845dbb07a9402509a388108
correction before objective
correction before objective
objective correction
commit 9759005bc72e6a077a225f7dc5d683652bb221e1
gradient correction
before handling scaling
scaling
check term1 objective
objective check completed
gradient for beta checked
gradient for beta checked
gradient corrected
gradient checked
gradient/hessian checked
correction completed
commit a6da3a852a7fbc570636866d586079e1f43dc346
objective2 correction completed
checked and before adding hessian update
middle of adding hessian update
commit a5412461512432d63428478b99a10f934ce311ad
commit 30838ed0026785e72419abf9ec0b2f0cbc594503
commit d82a4903fee2412231136fccb573e1e56a4ceb67
commit 5afc2e3d71132668d1650c0f89c61434f074df91
commit 8981c0eab28b6b4f86c33f7c18d949e36892df16
commit 95977e6103fcce42cc1a102cb7c3a56b13721fec
test convergence
gradient check
approx_hessian
commit cbb220c1e36056bc8b2d04b55904febb01e36c34
commit faae4c0047353b39c6b4ab0b396e1550aa2c686f
hessian update
hessian update
hessian update test
commit 97249f6d556fdd8ca0dd3628ec5c30af269c4576
commit d6575a076190dbf4cc3788a782e522e205fdfd41
commit 7ae5733b2e3b08c7ba6b8e664323be2dfd6f1ae0
commit 278c0d82686c06fb0030af357948f73ea67ed91d
commit 3d22888899ce6a2c1202a3a22675d91c6147aa6d
commit 22830dea6228b2bafcbd5aaa7ba99c348aeada4a
commit bf55cd32826cd83f6b7bdf4f56e62bae8143d24a
commit 6419f7596e31bc0650659442ed0b29ad8d1440e9
commit 673253d409fcc254b0d0b0b873dbe216609fa70f
commit ec2a18f24a38c38dd52acf65acc731a19460487c
commit 8097297df8e5856aa96cd577a4c79d59bf22e08f
commit face384930cb26b5e6a3ac50c34fe5137b3d73b1
commit ca851d8b2e558d4ddb39eb2dc7d13bbd8dd5f2b2
commit 100592cad6475addd910f0d8023b16db127ca8a8
commit f62f202a1392db4c45c1acd6216ec3feebb19cc5
commit 462f898ac6d1233dd922cd3bddfe2ef2455d27f9
eval added
commit 314643a89906652e7e5db7555c1d17e533e492ba
commit d8b01ff8ef81662ff63b0e5ea446830515dc8784
commit 3b1bd11dc100424cb51629c9443044e914d30ac6
commit 9747c63ea5d3726074995472a16236bb10b98ef7
commit 7d0d93392abc6b589e564ba4b44bd7f63f0d01a5
Some changes in opt++ for soyeon trust region
getting closer
now it compiles
commit 5cb66d44a1185baf76c8b9d9e88446a5a6bcf4e0
commit 456335121b1826728349d499d6723c1ef47bf933
commit 6a2e2e5d77c13dafa2f467c8ba889a7216ebac1d
commit 2d6fbb8da94d84a78971a4244abf5782638fe1da
commit 8aca707be86231c103f87ea0fe9e73b67136af52
sgm2
09_04_09
commit e1eee3912d544e17f62fc2aa754f8293f57cbe8a
commit 850657c502162114d3a806a2024114ebc696ece8
grad_norm 0.001
09/08/09
ddcm det alpha
ddcm2_01_23
commit 83f51a63ab5fa6209ff3747a4494a2bdb944be23
commit 28e6fe2dc8ac2a002f0bdae1b48d615b4d2d29f9
commit 00a42f17001b5af6a2e866323cde280d2521ac54
commit 3d24c74d43446b6ded8bbf3ded70f5a7bf1ba7a7
ssharfraz3 (14):
Added Boost program options for command line
Added Boost program options for command line for allkfn
Added Boost program options for command line for allknn
Added Boost program options for command line for allknn
Added Boost program options for command line for naive_bayes
Added Boost serialization for ArrayList
Added Boost serialization for series_expansion
Serialization to fastlib/src
Undoing serialization for matrix as of now
commit 574ed5246be72ad6a1a32193244f981bed01030c
commit 52445dd863b5d9147a2c626aa862e1ee3d6ae4a5
commit 848718dc300af49d70de45956c9ea26876dce816
commit f4d43965c81471fccd45cf8e2f09039d491ecabb
commit 1d9d3c1cdf47752c1af777debd145ce65d3770fa
stereomatchingkiss (40):
1 : add function Serialize
make codes follows the style guide
1 : remove inputSize from the constructors and data member
refine test cases
1 : add read only function FeatureSize
fix bug--return wrong feature size
fix vc2015 compile issue
fix constructor bug
remove data member epsilon since it only needed by constructor
fix bug--forgot to initialize parameter scale
adjust format
first commit
add example
add example
add the link to UFLDL
add the link to UFLDL
refine comments
1 : Transpose the input
can adjust the output range
adjust format
extract the part of encoder
use arma::uword to replace int
implement command line programs of softmaxRegression
refine messages
1 : change file name
1 : change the option name of command line
make MaximalInputs become more general
fix bug--range error
fix bug--sign error
first commit
fix compile error and comments
Merge https://github.com/mlpack/mlpack into visualizeEncoder
1 : add function Ratio to set the ratio parameter and set the scale parameter
change Predict to const function
const correctness
1 : change ColumnsToBlocks from function to class(place in core/math)
first commit
refine test case
able to set block width and block height
add new test case
sumedhghaisas (28):
added module 'lmf'(Latent Matrix Factorization) to accommodate SVD based update rules alongside NMF based update rule. CF module is updated to use LMF module.
Changing LMF(Latent Matrix Factorization) to AMF(Alternating Matrix Factorization). NMF and CF modules are updted.
* Modified AMF module so that now it uses tolerance checking rather
* fixed include error
* Added momentum to SVD batch learning
* Templatized termination of AMF matrix factorization
* Changes in AMF abstraction, Termination policy is made first template parameter
* faster implementation of SVDBatchWithMomentum
* modified termination policies
* error in SVDBatchTest resolved
* added SVD Incomplete incremental learning
* added local minima storing functionality to termination policies
* Added convergence test for SVDBatch and SVDIncremental learning
* added svd incomplete incremental learning tests
* remaned SVDIncrementalLearning to SVDIncompleteIncrementalLearning
* added plain SVD factorization - wrapper of arma::svd for CF module
* added tests for PlainSVD
* changed row_col_iterator::operator-- implementation
* modified PlainSVD module to return normalized frobenius norm
* minor changes
* changed PlainSVD to SVDwrapper
* added documentation to all update rules
* added AverageInitialization to AMF
* added NMF, SVDBatch, SVDIncompleteIncremental and SVDCompleteIncremental to CF executable
* added AMF tutorial
* added AMF tutorial to index page
* Adding support for user cleaned matrix in CF
* Refactoring CF module
tekhnofiend (711):
added dir niche
changes in .../u/niche
changes in .../u/niche
added .../u/niche/entropy
moved some stuff, nishant
moved some stuff, nishant
updated .../u/niche/tree
minor
updated strategy.pdf
added bi_fdkde.cc
minor
minor
updated niche/tree/bi_fdkde.cc
minor
changed strategy.tex to entropy_l2e.tex - nishant
del
added tree -niche
cleaned up stuff - nishant
added more spacing entropy estimators
updated jackknifed_m_spacing.m
nishant, added efficient jackknifed m spacing estimator
added spectral project - nishant
added nn_cube.cc -nishant
nishant
nishant
added functional_ica.tex -nishant
added .../entropy/scratch -nishant
nishant
updated functional_ica.tex -nishant
updated functional dir - nishant
nishant
nishant
nishant
nishant
nishant
added fMRI sign SGER
updated fmri sign sger
added niche/fastica
added stuff to niche/fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated funcica.m -nishant
corrected funcica.m -nishant
added s1s2.mat -nishant
updated niche/fastica
updated niche/fastica
moved stuff from u/niche/functional to my local matlab toolbox -nishant
updated niche/fastica
added niche/fastica/TODO.txt
niche/fastica now has symmetric and deflation versions using logcosh, gauss, and kurtosis contrast functions
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
added fastica_full.cc -nishant
updated niche/fastica
finished coding fastica -nishant
updated niche/fastica
deleted unnecessary files - nishant
updated example
updated niche/fmri_sign
delete stuff from niche/fmri_sign
delete more stuff from niche/ASL_sign
changed assert to DEBUG_ASSERT in textfile.cc
updated niche/functional
niche/functional - changed names, added test script -nishant
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
added centering function to niche/functional
added get_scores.m to niche/functional
niche
updated niche/functional
updated niche/functional
added s1s2_10.mat to niche/functional
added smoothing.m to niche/functional
updated niche/functional
updated niche/fastica
updated niche/fastica
polished niche/fastica
updated niche/fastica
added niche/RADICAL
updated niche/RADICAL
updated niche/fastica
updated niche/RADICAL
updated niche/radical
updated niche/radical
updated fmri SGER
added niche/fastica/fastica_stylish.cc
updated niche/fastica
updated niche/fastica
deleted old fastica -nishant
updated fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated documentation for niche/fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated fmri sger -nishant
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
updated niche/fastica
finalized code for fastica -nishant
really finalized fastica -nishant
deleted old_fastica.cc
removed Doxyfile in fastica
deleted test_lin_alg.h
added a verbose message to indicate what IC we are on during deflation approach
updated fastica_main.cc
updated fmri
updated fmri
updated fmri
updated fmri
updated fmri
updated fmri
updated fmri
added tbi to fmri -nishant
updated tbi -nishant
updated temporal ica -nishant
updated temporal ica -nishant
updated temporal ica -niche
updated functional ica -nishant
updated functional ica -nishant
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional;
updated niche/functional
updated niche/functional
updated niche/functional
updated nmf -niche
updated nmf -niche
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
added results_gene to niche/functional
updated niche/functional
added k_fold_fpc_cv* to niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated niche/functional
updated
commit e1228503789ddce6cff5a7a0ef9c8c2071a9fb29
commit 7f6cdcd037e2124d1aae08b05851a4f7882ed13f
added pica
commit 42b1f704e1405a662b99707e55fa59a70e95fdbd
fixed
commit dfd10bc6598d0fbc2d9753dccd4cacc256794731
commit 802468d0178b26a4466f9f2b8e97c90b3a670071
commit 27f49df779681ad7d589ffdf8a0dcab8726f604a
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commit ee5d80d333368e3c105cb74fdf9bbf1ced85869f
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commit ca8a0510834df8586af5ff7252d79a73b852762f
commit 07ae88c052a465e5d40aaa57a5f65edc97459e22
commit 27f129ce202f6e9316a3c4617e513844506d7e61
commit 0aea22a156265d4814bb1c74f452c2d570107786
commit df32d8f7239e68bb6ba1c499821e2ea1a1d5bca6
commit c60b25fa82642f738afadaab86d751d82e24367a
commit 3fd5d7dfb29e76314b3ded7169dde93701fa23ed
commit 22d4437713298a3b5343e84b9d4381155d4a5c8b
commit 04723d37860ad55fcd539cf4c176d153319ae061
commit 16b213d9880ebfd79753997db268ca5757579e0a
commit f258d1ae30a9df5c426b4a1fcee8c646ee651c93
commit 0be3de5cd0a38869a7ac79ce6dae2f693cf2d87e
commit 9513eb4ef255364fdc51c1858e720c54eb349095
commit 94c2f9889aebfb7acf27caebb83ab84bb904bbf8
commit 705b52b2af2af01cb703370389f4994acbe5573f
commit 479cdf1f7d50ae0e72f8a50b1dc7717db502dc1a
commit 3acb8f4d0fbb37e44f1bc35c1dee2717d4d8ea4d
commit a0105abd5a0a07355d6bac7de7e0efd2ebe4310b
commit 1a2646a46456c86b9cd3f8fc5b6285947c563408
added niche/spam
updated fnmf
commit bec053e9b460fcea454e37789e33f2e82b70415f
commit a1cc3ae531b89e1d0c8bd60fcf346492a805f1da
commit 9d0046aac8b9a2402b2a3f8c743d47a0f1b544bf
commit 6989db828a068887701365a234022b897f98d0f6
commit b5ec42b29be85fdb1b191ae6bd313a41e331e205
added benchmark_ica.m
added benchmark ica scripts
commit cc524a570edc2522f064e241a701b1e52ea9e651
created kkf for niche
updated l1reg_klr
updated l1reg_klr
removed kkf
added documentation
added contrib/niche/hshmm
updated hshmm
commit 20ed118450cd6b0a2e44fdf52fb485ce93c461d1
commit 8f8afd17974064f16a86976f3ed7081e1e497ead
added code for ObservableKernel
commit b42bbfb9e4cf33ed537b6ee704127c9bb57a12bc
commit 924b15c82501060fe3b075557727d155d72ffa67
commit 151b2ea9a5cf9e24891fa86af5b7fa7088c9c780
commit 7d2d108433247a251843d22e15e4ee9e209201a1
commit 47dea76c5c6f93f2474fd78fee63081235c59906
added niche/lds, preliminary
added code for multiple lds sequence generation and calls to zoubins stuff
commit 9698f87545dbca4fc533640b0676b01cfe09f22c
commit 8445d8806fe92b348ee4d8dd76a689236c307afd
restructured MMK code, templatized HMM, and added Multinomial distribution
commit 88fe1bad40c645aff9f832a96a6702664aa0397c
commit 33d9175118a1e16d5e3b532dc1c90132e938c872
commit 9831634b0b575ad5bc6d50d90965238803ff696d
finished load_profile and modified test_hmm_multinomial to compute kernel matrix from file-specified hmm profiles
commit 7ddee6c6292c1a4f1840027a3c58a2a7a044e26a
added stuff for hmm data
commit 9de1b9a6fcf896c06f4eb8c982238302eacf9098
commit 1c5f55d8c98de626843e88151c97a51a2eb00c26
commit 96ece25b87b36735644c88d8e0528c203a43da55
added kernel kmeans
added hmm_testing
commit c2c0db744b7bfc59577a9677a047c349f0c2002d
added niche branch of mmf
added niche branch of svm
commit 5f24de754f69f15a22bb9fcf4cfb158a24f1f6b8
commit d59772e32fb12c4042c0a104f0201766c7283323
commit ee34110437842a1d78fa3b9b0900f9dc7f00d042
commit 5a0f65de4a3f1fee67724e3febc428726cc31957
can save and load data for good testing
small changes to reflect rbfkernel->mmf
commit 1f43b62b0268065fd4d509bb90b0b24cd165636f
changed format of results
commit e573c744837bbd999d7c968f1178ce8a1fde34e0
massive speedup for mmk
commit a1e1e0663c7e5fcab458fa9d21d1c13835a4a9a7
added testing for array of C regularization parameters
made parameters member of module
commit 9668e15166ffb65feb56fc2676368d904a03d3c3
commit 072c97b485844d2e9a899ad01b1f8b2d2a6730ce
added kfold cv
changed documentation and minor param stuff related to cp and cn
commit c0e75ff15da158e44ba802602ad317e5a5d26aca
commit 1ad08b7331c606ff4dc861811079b58b690f34f1
commit 2e1b60b70f6fe5fd51d1f60097a3297130c550fc
commit f940f0a98aef3c5c5ba831c8dbc177768a123d4b
commit 3fbe96a298e3692ff3c3f17f6786e3ffdb17de18
commit fc288616746841ae96fde786f481edddce45004e
added hmm_generative_classifier
commit f3928b5cfad9b80dd3fafe303054a54510abd160
commit 874f8000f5af0a97ed6c7b37274ce88a41762ac8
commit 24266adafa8c5e40cad3a72a21273a6b503ab8b5
commit 5b76eddaf6394573d254a423c4f4ab25031c64a9
modified GenerativeHMMClassifier to save learned hmms
commit ed53fdc53300a121423971660ca02f25d5f6f13b
commit 58881f153b2f858ca2b3ba772f6ec07c0ca1054c
changed tolerance for smo to 1e-6
commit 9d58532b9899828293cc1b747d89aa9b768fe57c
commit 2ff6946a675edda5493593381415e30dfb7054cf
commit 65d0f513ea497dd32d4ce95db9478cb3a7e229a9
added niche/spike_train_dependence
commit 62f560365150017622b8d2beb5bd0961192137ae
finished code for creating points
commit d2d28baf8ff6f3edb99f57c564cfd67fa3e443ee
commit d873cf6b70665e51fba1c3b2bea0d54481efb1d8
niche - started new, nice hmm code
commit 6a3f62e548abcc9b82a436d8ef6e4066a04b9010
commit e1108fefc1c3fadd35f5359bba47a9335bc688ee
commit 0b9336877a942ff0234555b5030d05678297b404
zhmm compiles
commit b7ca883325a79b4dcaf8bc3fe9902342c8970378
commit 1054e79551e15b990b3d75e86ce1a663e2589389
commit 3dea7a9d32bf9a553701cc6da3486484789b1434
prelim testing for mixture of 1 complete
added diag_gaussian.h
added la_utils.h
commit 1e9c0b0a856a623067fe4c384eba95608b6a53ad
finished baum welch with testing, onwards towards viterbi
commit d744f40381bc5a740680fe9477a70358a0f3e5e4
commit a0390a4ca52fb054d88f8dfcf45fb0f48dff5961
finished first final cut of kmeans_nonempty code that uses MCF (minimum cost flow) solver from ZIB
commit 39a6b21690bfd46c27774558e010fb9daaf172ef
commit 6d1eeb757c64a0d94a2e7e99d58abf8dd8685575
more final version of kmeans_nonempty
commit afaccca0363cec349b371f348cddc7572c5f2cb6
commit d4bebeb52e04f1d405a9e5c4cd5a382edc9cf3b9
changed last argument of both CopyColumnFromMat functions and CopyVectorToColumn to const
commit d3166a4bb807a929cf8539e21b2657c79a75b4da
commit 8eae721ee2101bb31c8aa9171175b4e8ec6978dc
fixed memory leak in mixture.h
commit 621fe6211e41fae13b355a1d799428bb684796b3
I think the HMM implementation is complete
I think the constrained kmeans implementation is complete
commit e6998a3e16150a43b7a823b16be75048ba6d7649
commit 5b241ab3f08b815e8758685bd17e06a0e589c230
commit 01b75c375c2c72790e376342ab99850a0ab744ab
commit c7e1834293706805eed2427c560fa79d9a673adc
renamed zhmm.* to hmm.* and removed the junk
commit 5a975a97732a6277eea50d51e0aa73598625ef5b
commit 573cb1741d7375d1368783c85d72a1eef64684c5
commit a5e9713ad16601c89285223036ca20f945e81e06
prelim version of latent_mmk for discrete observations is complete
commit fc48d6e857fbff3df696f30de28d449e60c2e395
added generative MMK and isotropic_gaussian
commit 6955648f0216b53cd0d82b870fe187d05851955c
commit bc4942d1fd42b5bce66d15116061a2eb129f4051
added test engine for mmk and svm
added object traversal capability to HMM and Multinomial classes
commit c078b36949082f4f2daf91dec84dd4119548cb70
commit 523c8c03fc5bae8647dfe0ed40481c08bf51abe8
commit e34c98bb494e753da3701650d8c0cd65c461da44
commit 9980889cd3e76c0a6c45c701119b49276deef403
commit b1e9f8f870073b65d023f413ba7b50fae5bf2f51
commit 3b1a81dc3a8de411fb95b42e3d8db75150396724
commit 8e331dfb535a0c832ff14a65db78da4729502acb
commit 947383fcf3b9536565c393ffd24098dfc8078aaa
commit 03cad5a3845409844b87689512eddb70b32bd3e5
kfold cv for lmmk
commit c504d9810576be5240018b691223352a97b2a8d2
commit 31b1a80a84eebd256a4ee40d5c425195ddc26b7d
added hmm_kernel_utils.h
commit 8e6a7c55e7e95e8690417f8a78d89e01774ad666
commit d9e4018cc5a43f629fcbad4da7feea1c32ac408a
added test_inbio_kpca.cc
nearly done with test_inbio_kpca
finished test_inbio_kpca.cc
added niche/kernel_pca
commit 371a81be4a42c52c86cefee2a187b7afa9c81aef
commit faf223c5970bbee3f2908b38ed068be5d321c375
commit 4cead5a785fb3a2dd1aaae562b17b82baac52d36
commit fb81e4a9cda83122a19d2b77e26ddbcbc3d68fae
commit 053b938e9521252cba2b2fc65f7b273e3701b98b
commit 08afbfaed42d0f92efe149ee2d0426a71aadb18e
commit f400e523283a5ebe2cf6d73ae96c2aa33d69371d
commit 92cc972bf4ec1d03e77ee6711a30826fc38a8058
added .../niche/bayes_net_kde
commit 3016f8c36559c367d8d051beefcf00beecf39cce
commit 0b79411a2e8d14c7adfe972cdcbb87a8244e6071
fixed bug with Init functions of AllKnn which do not take module_in parameter - now module_ is set to NULL
commit 65ef1f57cc3b8c535efa909b579b33c0631f34f3
added loghmm.h - it awaits compilation and testing, added fmri programs
some updates to loghmm.h - nearly debugged
commit 0f9d8e8dd0ab9e6197631fa1f314d516f0b7499e
commit 1c0ad3615159d40e9ae882aca7ec80bef6bcd63d
commit 76f83dbc0fdd80bb687d1aa9e1b9dafbf3e8a1bb
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commit f33fd0175d7f941d5eaec24b1fe5eabfe6a29922
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commit af768cf62763a27a7ddff9e5ac7e59ca6dbd366d
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commit 061c5601f18185ec85dac6c1c724aa41a1740e52
commit 44104f9f3fc43d74301680e553794bf5ec1db724
commit 297b9376bba1be231ffacdf6be52332dc232d47c
commit 62a98d5b30adbc31e3271ee42355f5648dc7fb7f
commit dd0fc509f6678035c30a473128dd21775faa6f69
commit c83427ba68011cb78873c2e7137cd2018cc45020
commit 09c3e7ed6bcd105a27ea14c5a28adabb37bd70d9
commit 78a8ae9c57ab094337ff8735a911a4d8220de49e
commit 90df6b09ca9fefe43ebd96e401f08f6a8163af78
commit 95eeef07170cc0eeab0240ba9ca5da5519507280
commit 05d28d25d577a8a4a6b0807b439abb739912380c
commit f08e72b6ec54438850513b441a4f4b5bf5f31097
commit b6af4b75e6f6d1d4cc46f5a24ce8e1fd10918fc1
commit 802da070e92f8a98dcde3eff07e2326366ba8f87
commit fa85253958f1cdb4ad172a14fe752452e29d09e9
updates to ppk
updates to ppk
hopefully corrected bug in ppk of diagonal covariance gaussians
added .../contrib/niche/regularizedISM with mvu example of csdp
added write cvxmod program -niche
commit 74684d5b2dd19505aedec45e169c7ab279706023
commit 4315c824d460b05bd0ec148c085bc002718671ff
update to kernel kmeans
various updates to new_hmm
updates to spike train dependence
updates to regularized ISM
added initial dynamic time warping code - needs debugging
holy shit dont use arraylist with capacity version of Init
commit f20f3d76158386a8a36ae6c021a7f7b245936c44
fixed InitRaw member function of ArrayList to allocate memory for capacity, not size
changed dtw metric to normalize cost by path_length
dtw - final checkthrough
added dtw visualization tool
fixed fucking retarded bug in dtw code that was due to hard coding of time series lengths
commit 3e921bd2a6f2449bcadfd28ab51f3e30b8c25a2e
finished first cut of multivariate dtw
added straw man - nearest centroid classifier, yields 47 percent accuracy
better organized multivariate dtw and added multivariate dtw to dtw.h
moved dtw.h implementation into dtw_impl.h
added multivariate dtw that does one global align using Euclidean distance between vectors in R^n
small changes to how files are read in
updated code so that user can specify number of ICs to find via num_of_IC. Also, fixed bug in very final step where we forgot to transpose unmixing matrix W before multiplying it to data
finished with rough version of Least Angle Regression (LARS)
changed CMakeLists.txt to include lars
Lars class now stores beta path and lambda path results
added LASSO modification to LARS
fixed CMakeLists.txt by removing test_new_fastlib
finished coding version of LARS that uses Cholesky factorization rather than Gram matrix. Still need to test and tweak
made some variables private. improving style and modularity of program
done with LARS and LASSO. need to add modifications for elastic net
in process of making modifications for Elastic Net; have modified CholeskyInsert
in process of making modifications for Elastic Net
elastic net code seems to work!
added missing test.cc
fixed a line of code in CholeskyInsert function, related to solving linear system; now a massive bug has been fixed!
restructured program into lars.h and lars_impl.h and created library
added project directory for discriminative sparse coding - code is pretty much an incomplete skeleton so far
file renaming and class renaming, and added disr_sparse_impl.h
updated CMakeLists.txt
more code reorganization
fixed DiscrSparseCoding compilation errors due to class renaming
added accessor for active_set() for LARS, and changed the check for LASSO early exit to strict inequality from mere inequality, to ensure correctness of active set upon program exit. This last thing requires some testing still.
file renaming and stuff
file restructuring
made cholesky factor a class variable and now am able to return it
file reorganization
fixed some minor issues so code compiles
added discriminative sparse coding to CMakeLists.txt
finished preliminary version of stochastic gradient descent for local coordinate coding
some trivial change to main.cc
bug fix in lars; if all variables are active and we are kicking one out due to LASSO, before we would stop, but now we realize we need to keep running interations, since not all variables are active anymore
fixed a stability issue; no longer using clever update of maximum correlation. for stability, it looks like we have to compute it by doing an actual max operation over the correlations!
removed mlpack from library dependencies for lars
swapped out solvers; now using triangular solvers, and using a function I made called solve_trans; note that solve_trans does not exist
added preliminary program for experiments on MNIST
added mnist_main.cc, oops!
trivial change to CMakeLists.txt
added local coordinate coding - awaiting testing
added local coordinate coding project to CMakeLists.txt
fixed but where in the case of initial maximum correlation being too small, we still ran algorithm and ended up returing wrong solution. instead we can return immediately without running alg!
commented out some debug printf statements
added CMakeLists.txt file, sorry Ryan!
some changes to driver main files
added local coordinate coding to CMakeLists.txt
added mnist programs
added tools, which currently only contains a function for efficiently removing rows from a matrix (creating a new matrix)
cleaned up LCC code, it seems to work now
fixed CMakeLists.txt
fixed CMakeLists.txt
made lcc main.cc concordant with fx_init; we now accept parameters
added speed test to main.cc for tools
switched call to lars to use cholesky
modified LARS to optionally accept Gram matrix as parameter
removed a debug printf
modified LARS init functions so that they allow reuse of memory that originally stores input data
changed random initialization of dictionary to sample from unit normal rather than unit uniform
cleaned up test for removerows
added mnist experiment executable for lcc
moved existing lars implementation into old_lars, due to possible issues
added newly coded lars implementation
moved old lars implementation into isolated subdirectory
fixed some #defines and such in lars
fixed include file name for main.cc
minor changes to mnist_main and some changes to lcc_impl.h to handle multiple iterations of the optimization algorithm
added GetCoding function to lcc class, and created executable for testing synthesis quality of a dictionary
forgot to add executable for testing synthesis quality; now it has been added!
changed lcc implementation so that DoLCC does a final OptimizeCode step so that, at termination, we have a learned dictionary and the correct coding to that dictionary
small changes to mnist_main and changed local_impl.h so that it correctly outputs percentage sparsity (forgot to multiply by 100 (!))
added executable for discriminative LCC for MNIST
fixed bug in ProjectW
added code for Pegasos algorithm. have not yet implemented mini-batch version
changed list of bugs. now there are no known bugs
added pegasos to CMakeLists.txt of niche
added mini-batch to pegasos
changed mnist executable to use pegasos
added function to discr_sparse_coding to set w, and changed mnist_dlcc_main to compute svm loss via a function
changed frequency of iteration number output
uncommented projection step
changed prototype for LCC::SetDictionary so that passed in mat is const&
changed mnist_main to allow specification of initial dictionary
switched two usages of fx_param_int_req to fx_param_double_req since the latter allows the use of scientific notation
switched a few usages of fx_param_int_req to fx_param_double_req since the latter allows the use of scientific notation
fixed a horrendously inefficient minibatch implementation. now the cardinality-k-index-set sampler (sampling without replacement) is very efficient
changed neighbor_counts to uvec
changed display of loss in mnist_dlcc_main, now store loss results via fx_result, and slight tweak to SGD learning rate
changed discr_sparse_coding files to fully implement discriminative sparse coding, but not discriminative LCC. previously, we mistakenly had implemented some weird nonsensical hybrid between the 2!
added test files for dlcc
added everything for sparse coding
added sparse_coding to CMakeLists.txt
changed InitDictionary(filename) so that it accepts fullpath of dictionary and does not assume some directory exists
added mnist lcc test files
added some mostly empty files for sparse censorship
commit ad6a4e50c0859362a62e5ad1451482b2a23a16d3
commit 43b3ef7e9673690474ac5cd740f4f7910f02e02f
stub
commit b14368b4932257b3adae87b210d495bca9e70976
commit e62ef98b523a0135e3ab4b358c3836baebf9be9a
commit 73416808e91b6001c28ce1f4c673538d1b58d6a5
commit 03a298859958c850690ffeadf3eea28b6f2685cf
commit 3b8b34d65e9c9deb7694372ab0a2260faec80ada
commit 9cd4beefaa4e0f7deac89c93c38acef0dc3a615a
commit 79aa7413e3aca83dbd93399b611a5f4418d05a3a
commit 5a1b847337f9a53cc23d1aefb750f4c1db28eff6
commit 5d5043f255cedabbda9ba04ae74811ec1825dd64
commit 7bc76aa8b90e14998f43d80ee7c8eeb35a5ebf17
commit 3c7d41bc1d9998447d959760e906cfc7e58ddca9
commit 08c0568053c6f006aadf2e103c8a6dcdfb284301
commit 30b92dc1da7f15ce163f2264d51705ed3a5389e1
commit dfb7fd23c47d0371eeeb271bda9b00e322ebe895
coded update for variational parameters for q(z)
corrected E step (computing variational parameters for q(z)), made it work in log space to avoid numerical under/over-flow, and pushed it into a function called ComputePhi.m
commit 3a2a40166776270d424de2176be063b70ba969a9
commit 8bfcb9a58bf095781bbf79ed6833b7c2b98ab6d9
commit e027796ae2223fd706e13001574ac36844b8bed8
commit cb14d541a3df9e054c52715bf99d09a8cf75eed0
added gradient and Hessian computation for theta
added ThetaObjective
changed name of sparse_censorship to SparseCensorship
commit 606939c67759d7ae7228a6e1630ae82aafee759e
made a start on BetaObjective - need to address issues with storing the Hessian
changed ThetaObjective() so that it takes into account theta_bar. Also, added ThetaBarObjective so we can update theta_bar
created EtaObjective, need to fix the parameters taken by EtaObjective and BetaObjective
first version ready for testing
fixed small bug in BetaObjective.m
Fixed some bugs. It runs now, but EtaObjective runs for way too many iterations (perhaps due to higher regularization of 0.1 as compared to 0.01 for BetaObjective)
started on exponential family sparse coding implementation from Lee et al.s paper
Dictionary Updates seem to work; now to handle the sparse coding step
fixed bug in DictionaryProjectedGradient and ComputeDictionaryObjective - I was doing some computations incorrectly due to erroneous notes. I still need to handle the Armijo line search for UpdateSparseCodes (taking into account subgradients, somehow...)
UpdateSparseCodes seems to work
added some efficiencies and added function to compute full objective
made the code MUCH more efficient in various places
fixed a sign bug in ComputeDictionaryObjetive.m
added load script for tiny version of rcv1
isolated gradient computation for Dictionary of Poisson Sparse Coding to its own function, in order to make way for specialized functions for each exponential family (for the gradient and objective only)
added ComputePoissonDictionaryGradient (should have been added at the last commit!)
changed ComputeDictionaryObjective to ComputePoissonDictionaryObjective
fixed function name inside ComputePoissonDictionaryObjective.m
made some changes so that Poisson Sparse Coding has its Sparse Codes objective and Sparse Codes subgradient moved into functions
shifted more code over to Poisson specializations. think Im done now. Also, found major bug in UpdateSparseCodes, where we were left-diagonal-scaling the dictionary matrix by Lambda instead of sqrt(Lambda)!
commit 009593c05034e935aafec09e6ca64359f35edc1a
small fixes, mostly syntaxtual
renamed ComputeFullObjective to ComputePoissonFullObjective
made PoissonSparseCoding call ComputePoissonFullObjective
commit c5038115df78b3913f21fb263d98616cb271e55b
added functions for Bernoulli - need to check them for correctness tomorrow
lots of changes, put in Bernoulli sparse coding and added option to choose whether to do Poisson or Bernoulli
commit 0f83698a6fac1be01c60da85510c8c1ad856a7b0
commit 5efef8a5a141bf965c56741445428327cfa5c54c
commit ccf09e175e2e5fe682ed725ae87d908bd8c2148e
added functions for Gaussian sparse coding
added support in ExpFamSparseCoding, UpdateSparseCodes, and DictionaryProjectedGradient for Gaussian Sparse Coding
found major bug, we were mistakenly dividing the l1-regularization parameter lambda by 2 when calling l1ls_featuresign, but all other computations were not concordant with this!
mnist_sc.cc small change to shrink dataset for quick experiments on newtons method in the dual
added Init and armijo line search for newtons method in the dual
commit 5c436b179e313194bed39285ac0162a72b01a91f
commit 2ec810d3562267f9514ee62180a13c0f493bd103
commit 419134f4ca563f24d009959a4d99cda42d6017b6
commit 9e2516ea6847d37f3042ee596252f2eb78aaca4a
commit 374c2b26afb4ec7b169627f2f876167eff3e41e0
commit 9737d4b05e7c080d2edfb7488f1a3fcb1e7d6491
commit 05c0ca6a1740f7d5b0fd0ba0c5515c38667174dc
commit ac0222ffa0222d0de1fc724a5768a3eb082ddebe
commit 24600bb2aaa8f0c66bc8dea5e6f4380b229d17fd
added some plotting tools
commit 836f5d4bc666ecbc6b3199495b878099cf232bdf
commit 836cd76f405a43af62ddabbf74e63714466c5448
commit b9d5c53dae27ebab57bd5f245c4f1f2e334c467d
commit 5e8525b4744df53480c41c5d39ee605625f351e5
commit 2158a3729ab8392c5e2ec7da50f238ba12a7e5e2
added task sparse coding directory (matlab version) with basic blocks in place (lpsvm and pegasos)
added first version of TaskCoding optimizer
trivial change to TaskCoding.m
changed minibatch size for pegasos
now passing delta parameter to lpsvm, as it fails miserably otherwise
fixed way of sparsifying codes in generative model
enabled projection step, although I still do not know if this is necessary
added error computation
various changes to TaskCoding.m
added sparse perturbation versions of Gaussian Sparse Coding
added some run scripts
added code (needs to be debugged) for convex MTFL
added argyrious convex mtfl
commit 7fdad7cca159e354fa681461d357d80fb690317f
fixed
switched to LP formulation of one-norm SVM, in search of stability
commit fde20285a41b754fee765c87606e6a54ee2560b0
added pegasos minibatch without replacement (bouttou style)
commit 67f0df2d6cead8f6b6f44002c6b5222556df8899
commit 817d7334ffc466f8dd5ce05fefe7975da2169f60
commit 617fe13affaeacba0efaa1a896251cf2364f4145
fixed bug in Learn.m where we accidentally have the same variable name, n_iterations, to represent both n_iterations to run convex multi-task feature learning and pegasos
commit ac986a1c3dc05aacfa46590db084ba938deeb50a
commit ac10b79eef6f5ee2df5b11fb210f58580dfb2e52
commit d27a1edc5e7c81fb0f49785e14ef43475856d08b
commit 033a4f095135c3d59cc75e3cb04fdc1fda6eda3f
commit ee2bcb15f62d971ee1e7fbf29957837285d45dc9
commit 3ed22b5651caca29b370d0beee4c76ab78ad9c23
commit 00ece1f666f6ed5f317fe286af9ea8a539bf44a0
commit 41340bdebac71c851dbfd08b8ab7da36549142e8
commit 60026104619bf1929104e8bcea9a03042050667f
commit af6a478f1f2dc9ba16775b59248ade947990de13
changed GenerateSyntheticData so that all atoms are unit norm
temporarily changed TaskCodingWStep to use svm_lower_bounded_margin
added svm with lower bounded margin
added pegasos with lower bounded margin
commit fb5b4004ef4726df16aca3392212795627887939
commit d53aef601575dc43329908ceb3daa29ed0d87977
changed some display stuff, and now normalize initial W so that each col has unit norm
faster, via precomputation of X * diag(y)
display aesthetics changes
added display of sparsity and nnz for Q
commit 47251b6d38e98f83efd2c276a0197f0f697ad276
added preliminary version of censorship experiment
lots of changes, including loading of bush half censored dataset
added lars, mostly due to Karl Skoglund and Jingu Kim
added Gaussian Sparse Coding using lars (with simpler code that does not generalize to expfam case, as well as perturbed version, and MTL version with perturbations
added negativity constraint to dictionary perturbation
added active set algorithms for nonnegative least squares with l1 penalty, as well as nonpositive least squares with l1 penalty (both algorithms are nearly identical)
added same as last update but using cvx (probably a lot slower
added function for censoring based on some proportion of occurrences of top 10 words in a given topic
forgot to add this objective function
added another censorship script
commit 398825e81adc0f9ab5423aa09e59d0382f5fcba8
commit c25fb56a7c52f40bf53b6ba391f86334da091236
commit ebfd37f7e196a2fc9af00476ad8b8788b37cd821
commit c85e6e40bf1388d0468b15226e110a228981bf33
changed CMakeLists.txt for radical so that compilation works in .../mlpack
added radical to CMakeLists.txt
Apparently an adversary swapped every occurrence that should be data.n_rows to data.n_cols and vice versa. This has been fixed, and LARS works once again
added LARS tests, but still need to make small changes before adding to CMake
added test cases for lars
commit 9d7bfce6a6865c1a827c6a792e8ece1f8295ac11
various style fixes to radical
more style fixes
I think I fixed two bugs. need to check tomorrow
we no longer store the data matrix matX as a class member, we changed the call to WhitenX (it is now called WhitenFeatureMajorMatrix), and added comments
put Radical in namespace mlpack::radical and moved WhitenFeatureMajorMatrix out of Radical class but into mlpack::radical namespace
added lots of comments
small fixes to radical_main since we present radical with a n_dims by n_points matrix
made some speed optimizations via manual profiling
some speed optimizations
added data needed for Radical test cases
commit 9b236c843b5ea5760e3dea285e83b10d7938e990
updated radical main
added test case for radical
added radical_test.cpp to CMakeLists.txt for test cases
updated radical_test.cpp to use data::Load rather than .load
fixed small filepath bug
you can now set the input and output filenames, as well as the options, as paramters
cleaned up lars_main and added command line options
stylized lars
removed unnecessary files
removed unnecessary file
fixed CMakeLists.txt for lars and switched from _impl.hpp to .cpp
commit c145a37573d34b318b316cdc08debf306b6e2491
many style fixes, made some functions private, commented out some unused functions
cleaned up lars
LARS no longer has X and y as class members. They are passed into the main computation function DoLars
updated lars_test to reflect changes to lars
increased tolerance for RADICAL test
removed random seed from radical_test.cpp
added some comments to LARS
more comments for lars
penultimate set of lars comments
moved accessor definitions for LARS from lars.cpp to lars.hpp
corrected elastic net / lasso objective function in the comments. I had forgotten to put the 0.5 scaling factor on the reconstruction error part of the objective
added sparse coding
commit 1275bafa43a1e245eba7663caf6457e4ccc8a6e5
added small 500-point version of MNIST
fixed CMakeLists.txt to reflect correct demo program name
fixed small bug in lars: sometimes after kicking a dimension out of the active set, we also need to explicitly set the corresponding coefficient to zero. In that case, we were saving beta to the end of the beta path before the fix. now, we save beta after the fix. This fixes a bug
fixed a bug in how we were checking the optimality conditions for the LASSO. holy shit, an error in the test case itself!
added test cases for sparse coding
updated path to mnist file
added modifier (setter) for data X
added sparse coding to CMakeLists.txt
added sparse_coding_test to CMakeLists.txt
added local coordinate coding to methods
commit 5edaf7d77e68c5ab67542604349789394d24efd7
added local_coordinate_coding to CMakeLists.txt
added tests for lcc
removed some commented code that no longer is needed
when useCholesky=true, we now use a once-computed Gram matrix for inner product computations between points. If one is calling LARS repeatedly with the same data X (as in sparse coding), one should use SetGram even when useCholesky=true, and in particular, it is better to use SetGramMem
Switched to Cholesky-based LARS. this version of LARS now uses Gram matrix in some places. We use SetGramMem rather than SetGram to avoid copying Gram matrix unnecessarily. Also, removed some commented out that was quite old
added some commented out debug statements
added back in accessor for matUtriCholFactor
modified OptimizeDictionary to return norm of gradient of Lagrange dual (with respect to dual variables)
fixed test for sparse coding dictionary step - the dictionary step now runs for more than one iteration, and the check is to see that the norm of the gradient of the lagrange dual (WRT the dual vars) is sufficiently small
theSundayProgrammer (4):
Compiles on VC14
mlpack build
Serialisation tests pass except DET
all tests are passing
tqlong (127):
commit dffbf8bacd1d69ec03d74b24989d0408810fb4b9
HMM codes
HMM codes
HMM codes
HMM codes
HMM codes
HMM codes
HMM codes
HMM codes
HMM codes
HMM README
FX compatible update
resolve deprecated functions
graphical models : basic data structure
tqlong: graphical model : sum-product algorithm
tqlong : graphical model - bipartie graph template
tqlong: Graphical Model: FactorGraph to be template
tqlong: Graphical Model: move definitions to gm.cc
Quic SVD error incremental update
QUIC-SVD tested on small matrices
QUIC-SVD bin rule quicsvd_main with command line parameter
QUIC-SVD doxygen documentation added
QUIC-SVD add timer
QUIC-SVD add timer to fx documentation
QUIC-SVD small changes
QUIC-SVD add lapack svd run time
QUIC-SVD add lapack svd run time
QUIC-SVD add relative norm difference
QUIC-SVD small change in comments
quicsvd_main with exact error estimate to be compared with the algorithm's estimate
kernel matrix generator
kmg
kmg
kmg
kmg
quicsvd_main add S*VT to output options
quicsvd_main add S*VT to output options
quicsvd_main add S*VT to output options
quicsvd_main add S*VT to output options
add polynomial kernel matrix generation
MMF
MMF triple
MMF triple states
MMF sum to unity
MMF sum to unity
hmm
hmm
hmm
hmm
mmf
graph
graph
graph
optim
lbfgs
svm_optimal
svm smo
svm smo
svm smo
pso
kfs
2dPCA
2dPCA project on major basis
Passive Aggressive
code separation into more cc and h files
code separation into more cc and h files
add cross validation
noob test CMAKE
noob test CMAKE
affine NMF
anmf
anmf
affineNMF image_type
affineNMF image_register
affineNMF CMakeLists
tqlong CMakeLists
affineNMF register_all
affineNMF ANMF_test main
optim::NelderMead
optim:GradientDescent
optim::L-BFGS
optim:L-BFGS
Graphical Model
Graphical Model
Graphical Model + BOOST
Graphical Model + BOOST
Graphical Model: variable belief + factor average
Graphical Model: Message priority
Graphical Model: Message priority
commit 8aa7b267a3cf33a4da1f207320f66d9d55e5dd2b
commit 36efdade0d5b66acc89c6f2f48662c639295a38f
Graphical Model : message pending
Graphical Model : message pending
message pending
commit ce284cfe5659e4a43f87b0d60be7c973109671e7
commit b1e34f818912f29453973d1388fe83e4d800d0a6
Revert CMakeLists.txt
add parameter --method to gm_test.cpp
Adding --iter & --ctol to gm_test.cpp
Affine NMF: graph matching using Hungarian method
Affine NMF: graph matching using Hungarian method
Affine NMF: graph matching
Template for maximum weight matching in bipartie graph
learning Qt codes
learnQt add KeyEvent to mainwidget.cpp
learning Qt translator ZH -> VI, some shortcut key added
Graph Matching: edge detector
auction algorithm for assignment: drafting forward_auction() function
auction max weight matching - done forward Auction
auction max weight matching - done forward Auction
auction max weight matching - done kd tree with median splits
auction algorithm using kd tree completed
auction algorithm: start allnn dual tree
auction algorithm: start allnn dual tree
auction using kdtree: command line parameters
auction: kdnode
matching : kd node with statistics
matching: single tree
matching: auction templates
Nocedal optimization method for machine learning, implementation via Boost.MPI
cross-match read data file
cross-match calculate run time
feature selection using submodular function inducing norm: started
l2loss l1reg
l2loss and logistic loss
l2loss and logistic loss
adaptive Lipchitz constant
vasiloglou (476):
first scheck in
added some more files
removed some files
commit 0da2d15efaa4f63819ba03879672bd31522fd66a
Working on it still
HyperRectangle unit passed unit test
added a new file
still working on it
still working on
node test compiled
still working on it
node_test passed
still working
Switching from TYPELISTs to stucts
Still working
close to compiling
compiled
finished binary dataset iterator
Building trees seems to work
Tree building works
Single tree methods are running
Possibly AllRangeNearest is running but unit test doesn't
Unit tests are passing with success
Added timit
Added some files
first check in seems to work
first check in
added to the repository
Close to compile
Find out how to compile sigsegv
Ready for debugging
Fixed some bugs
Partially runs but the paging doesn't work properly
Unit test seems to pass correctly
removed some printfs
put everything under a namespace
Added namespaces in the allocators
fixed it so ti can link better with fastlib
Fixed some incompatibilities
Added a build file
Improved build file
First check in
Added a build file
Fixed build file
Trying to use both engines
Making it compatible with both memory managers
fixed the test, it is running properly
the test is running properly
All unit tests are running properly
Everything is running smoothly
Now all the tests are running fixed some major problems in the tpiemm
I had forgotten the build file
Fixed a bug for all nn
more bugs fixed
doing some optimizations
fixed some bugs for the tpie memory manager, still the overhead from the access is very high
I am trying to build a balanced tree
hrect_test and node_test are passing with the new lock method
trees are running very welllllll, passing tests
fixed a few bugs
fixed mahor bugs that woudl stall the system,
fixed the bug for SIGSEGV
Major revisions, I added the knn_node , trying to figure out whether
Compiled
Made major changes so that it can accomodate for different nodes, node and knnnode
Seems to be running
There was a fucking bug that took me 5 hours to find
Removed memory locking from memory manager, because it creates problems during tree build
Changed so that we can input big integers from the input
minor changes
fixed a minor bug in collect newarest neighbors
Trying to make the balanced case work
Made speed up in memory_manager_with_tpie
Improvement in the TPIE MM now it works faster
associative memory
A bug in collecting the neighbors was fixed
Haven't tested yet whether the balanced tree works but at least compiles
Collecting results in test files
Minor bug
Forgot to add build file
forgot to add it
Garry changed the the Vector alias, temporarily not working
Added documentation
Something is wrong on heater
Printing the command line arguments
minor
We have to set Knns=0 in the reference tree
Compiled
better
first checking of the proposal
commit 83164b34551c4a1cb7c4a2625ae0fd7285d55735
commit 02624b75eefaf057e732969d51378836fc170f77
added intro
added the paper on bandwidth tuning
more corrections
more
added some figures
started adding figures
getting closer
have to write more on work remaining to be done
commit e824a36e4b81dbf594adffbe37dabab7e93b99a3
wrote more on semidefinite
one more section to finish
remove some temp files
close to first draft, Speech recognition is left for last
added bib file
references added in the manuscript
getting there
tables added on cache performance
several changes, fixed images, changed title. Looks more like a document. Ready for proof reading
one step before submission for revision to Alex
almost ready
some more edits
Added Alex's comments. Ready for the final review
before the final review I need to fix some references
after Kelly's corrections
Submitted
added the proposal presentation, still draft
getting closer
incorporated some of Alex's comments
This should be the final number of slides
after second alex's comments
commit f1cc8f8ee759743982988b9ec6dc406c8a96c4e2
added the flash animations
added more flash
converging
almost done
nearly ready
corrections before the first dry run
more corrections after the first dry run
before alex
integrated Alex's comments
more corrections
before dry run in fastlab
after the dry run
before the official presentation
minor updates
first check in
before antonios results
almost done
commit cdcb526194282a47a813bcd788883db6dcafa5c1
commit 2fd0e8fc6f034cb6ee71888b961030e8f405c47f
commit a770c616e970f649285ba7cb31d7d8d4326b5694
first checkin
this version of max trace is running. We actually needed to scale the objective function with something small (a*Trace(X)) a~10^-4 so that the dual becomes feasible.
working
removed binaries
added swf and wmf
commit 9748b8b19744c2f5d05a6b956da9e9f1e76149f6
commit 72676713b4b666fb84c27446801fdb793eef1d3e
first check in
First check in
decided to add sparse vector
close to write tests
getting closer
not compiling yet
compiles but doesn't link
sparse vector unit tests running
:
compiles but it doesn't link, there are some undefined links
compiled !!!!!!!!!!
sparse matrix works now, unit tests compile
added einvalues but it is not 100% functional yet
This is the first check in of the trilinos package
removed a binary file that was accidently checked in
This one is perfectly running
added more functionality
Compiles but it doesn't link because our blas library is missing
some minor corrections to the headers
added the clapack and cblas definitions in the la namespace so that they do not conflict with trilinos
implemented the rest of the multiplication. I also need to implement
added ifpack that does the factorizations that are going to be implemented
Added complex routines for blas lapack but they compile as a separate library
now it links with comples blaslapack so that everything works perfeclty with trilinos
changed Epetra_ConfigDefs so it looks for Epetra_config.h in the same directory
Eventually working, links with all blas libraries and the headers have been corrected
eigensolver works
allmost running, most of the test except for basic operations are running
fixed the copy constructor
all running, a small correction in the copy constructor needed
everything is running !!!
This package works
added all the neccessary files with the appropriate modifications
added incomplete Cholesky factorization
fixed ifpack_ConfigDefs.h so that it compiles
Trying to make things compile
compiles
major bug the sparse_matrix.h was linking to the incorrect version of sparse_matrix_impl.h
It's working
Made the autotuning for eigenvalues
Added a simple bandwidth estimation routine
Added LLE but not debugged it
changed the style
changed the style we need to fix the eignetest
Added the allknn so that I am compliant with fasltib
it is running
added the test set
close to run LLE
runs but there is an instability in
corrected so that MultiplyT returns a symmetric matrix
minor edit
minor edit
Optimizing the eigensolver
Seems to work although LLE gives a singular matrix
Added a function to export to a test file
fixed some style
doxygen is working now
more unit tests are running now
1)Fixed bugs of addition and subtraction
I changed the way get works after fill complete
Added more documentation but I haven't fixed the code after changing sparse
major bug with set fixed
fixed major bug in makesymmetric
Made sure that the pencil has called EndLoading
Added least square fit with the unit test. It is just a simple application
Working version of allknn
Made it a little simpler
changed it so that it links to the allknn library
fixed documentation and doxygen
final version
Fixed some bugs in Copy constructor
fixed some bugs
changed the documentation a little bit
fixed some potential bugs now that sparse matrix has changed
fixed copy constructor
first check in
minor edit on the build file
compiled
it is running but the optimization error is increasing instead of decreasing
major revision
seems to run although it needs to be cross tested with a swiss roll example to
I had forgotten to add the test
it seems to me it is working, it is just a matter of tuning the parameters
it seems to work
finished the BFGS
ScaleRows works with a matrix too
BFGS is not running properly but we are getting there
Fixed the query=reference case
it is running all bugsfixed
it is terminating now
it doesn't give the expected results on the swiss roll
It works suspiciously
this one seems to work
commit 6e2a04cb3dd6e9a038dc8aab228f46bb55d49791
changed from armijo to wolfe and now it works it is much more stable
commit c51e54c8a84600ed615d69428031cee894e19531
Added a maximum cap for the infeasibility
After a major reorganization that didn't necessarily give better code
compiled
uo and running
changes in the cap
Compiling
Remove some binary files tha accidently were added
test seems to pass, we have to check for the validity of the results
It is working
some minor modifications, tests seem to run ok
several bugs fixed
fisrt check in
Some minor repairs
Implemented the member functions
Added some extra files
more
Added a recorder for the final results
compiles
I need to get rid of some warnings, it is running
There was a bug with the num_iterations that wasn't initialized
Trying to solve the submodule issue
Eventually it worked without warnings
Now the submodule works better
fixed a couple of bugs in the max furthest
close to automatic tuning
auto tuning seems to work at least for swiss roll
Log the lower bound for optimization
auto tuning on
fixed a minor bug
fixed another bug
fixed the initialization of LOOCV
fixed the same bug
added pca preprocessing
first check in
few corrections
added the example for memory_manager
Fixed some bugs and passed a simple test
Still working on the dual manifold
Seems to compile , I have to remove from svn at some point
Test seems to converge.
created an application for working with the movielens
Removed these files that were redundant
Making it more natural
results seem promissing
some minor fixes
I have done some development on L-BFGS-B
fixed some issues with svd
hasn't compiled yet
it is running
changes the way midpoint is computed.Added a function that overwrites on an initialized vector
development done, now it is time to compile
compiles
some trivial parts are running
doing better
still is not faster
Getting closer
first commit
added more files
close to compiling
compiled but doesn't run properly yet
fixed the error in the gradient now minimizes
it seems to work , needs to add an svd on the results, svd on matlab showed positive eigen_vector
it is running now!!!!!
it seems to run very well for rank one only although I haven't checked the results
Put the code in order, and ready to play with the original formulation
It turns out SDP with rank one gives the same error with just simple NMF
changes name
Our last attempt to make sdp nmf work
addded more files
compiled
gradient gets nan, probably because somethins is unitialized
now it looks more stable but doesn't converge yet
it is running for a small matrix with 31% error and it seems to me something is
extended copy for matrices
the convex mvu is sort of working not sure yet, the results are poor
some problems resolved, the barrier is not working properly, there is the problem
the bug in the gradient was found now it is working but it seems to me that the minimum has a lot of points
extended nonconvex nmf
Corrected some depreciations
Fixed some depreciations
Fixed some depreciations
Added geometric nmf implementation too
added a directory for disk allnn
Introducing disk trees and advicing
This version works and records correctly the memory_usage
Fixed some bugs in the memory manager Advice and I fixed some bugs on the trees
Added support for large datasets, it loads them with StaticInit that maps to mmap file
Put it under fx_module
We needed a code for allnn
Added the test file in the repository
Traditional allnn
Minor update
Further changes in the tree
Median splits seem to work
Updated to the latest fx.h
Fixed some warnings
Fixed a minor warning
There was a problem with kdtree_mmap_impl.h in general this part of fastlib is not well developed, kind of hacky, it works now
Additions for Nadeem's requirment made, they haven't been tested yet though
It seems to work although I think the file is not a good one
Added the golbal optimization nmf files
Close to compiling without errors but still a lot of debugging is waiting for me in the logic part
Close to compiling without errors but still a lot of debugging is waiting for me in the logic part
Need to put some extra progress notifications and we are ready to test
The algorithm iterates, doesn't crash, we need some more work though
We have the first demo running, we need to improve on the initial boundaries, as it seems to me they affect
Some minor modifications on the progress reporting so that it is really silent when the silent_ flag is on
Attempt to make it mac compliant
Attempt to make it mac compliant
Added some documentation for the annoying warnings
I tried several things but it is still slow
Dummy
Compiles
Tighten bounds almost works, we need to take advantage of the fact that non-convex case gives a good lower estimate
Tightening works but doesn't give any better bounds
Improved a lot
Compiled
We do have a functional nmf executable running experiments for the paper
fixed the problem with the destructor so that it doesn't cause a memory leak
Just one compile time error and we are ready to test
Compile passed
Seems to run the first steps, but we need to change it so that the splits on h happen soon after w, this might give a better solution
we are getting closer to the global optimum
New version, trying to avoid oversplitting
Still haven't found what I am looking for, need to work more on the last method that doesn't work
Corrected some problems with the tree depth
Need some more effort to compile
Need some more effort to compile
Compiled
We have some progress but it is not working yet
We made it obligatory now for the optimized_function to have a GiveInitFunction, it makes things easier
There are still bugs but some were found
we almost got it close to working
It is more stable now, but hasn't worked yet
It is more stable now, but hasn't worked yet
We keep findingbugs here and there, scaling doesn't work yet
Some extra flags to lbfgs so that warnings are not whown
It's the first time gop seems to work very satisfactorily down to 0.4% error rates
Changed the lapack installation so that people can use their own or just download it from netlib.org
Fixed the bug so that it doesn't ask the same question when compiled outside of la
Fixed a problem with the lock file
Close to compilation, we just need a function to initialize the matrix
Fixed a problem with the new_dimension
Seems to sort of work
Compiled the svm now I have to test it
Still not running properly
There is something strange the inequalities cannot be satisfied
Added some datasets for validation
tracing errors in the lagrangian
"seems to be working I need further testing"
Problem solved for the moment, the whole problem was with the lagrange multiplier. I had to increase it
Things seem to work, but we have to put something on LBFGS ao that it shows whether the goal was reached or not
minor modification so that it handles only manifolds
some things that matter. I had the problem when the labels are in a row vector and not in column
Added two more datasets
Added a file that has the run-time parameters we use
disabled writing on the disk
Added an executable that computes knn, need to add documentation though
Added a utility program that computes all k firthest neighbors
The single tree seems to work with the tests
Some minor changes
Implemented the multiclass separation maps
We extended the separation maps so that they now can accept text files with the neearest and furthest neighbors
Fixed
Trying to integrate opt++
Finished first stage unconstrained optimization
Still compiling
Still compiling
Compiles but doesn't link, need to instantiate the static member objective
Now it compiles
seems to compile, it doesn't converge to a solution possibly due to an error in the gradient computation
Test for unconstrained optimization passed
Constrained optimization compiled, it needs to be further tested, also I have to examine whether Hessian comes initialized or not
added data files
Still lapck doesn't compile for cygwin
Fixing lapack for cygwin
commit e4df1d175ad8835c1adfc6441304629c786be9b2
commit 6990e91e5a07f1717a68e4b70ec5516c45d8cda3
commit 179d0ebc10e32ff553da181c02d5f0f55582774f
Now blas/lapack works with cygwin
Fixed some minor bugs in mvu
demos added
commit d58db8775bf09ec591fead33ee4c103cb1f19849
commit 57179000e9e4bb0550342be2a6e486dfcdd77cc9
commit aa74c9648ebe0ecd30bb25028e1532e001f613e3
commit df4f02fbee2ba614480b3efd36fe31fd1dc99e09
Reorganizing the optimization directory so that I can push MVU and isoNMF
commit a1fb7ad3727de96c344e89a15eabcb3dacfa8912
Restructuring optimization
changed the names to comply
This is where mvu and isonmf will come
Keep fixing mvu so it is releasable
new user
a small bug in the build file
It compiles now but I need to add more documentation
added documentation
added regression and ridge_regression
Added the necessary files, now I need to compile and test it
added an extra utility on the matrix so tha you can create diagonal matrices
it compiles
seems to be working
Ridge regression is working, I added a main file too, so that it can run as a
added cross validation and eveyrthing is based now on SVD
fixed some stuff in the documentation side, so that it becomes easier for
automatic installation of opt++
Added significant amount of documentation.
fixed Doxygen a little bit
Moved the optimization under fastlib
Fixed MVU after moving optimization
fixed some minor things on the build file and added an extra namespace for optpp
This is going to be a working version of the comercial fastlib
testing copy
I did something wrong
This is fastlib3 for prefection
finished first stage I need to write a test
some minor additions
nearly there a big effort to templetize evrything in linear algebra
still developing
compiles
Templates in la are workoing now along with tests
I had forgotten to add this file
added a big collection of utility functions
haven't tested utilities yet but coding is done. Thinking about extending
More templetization of the la domain
Temporary commit so that we can move to a new repository
"fixed a trivial bug"
sorry about that
commit cf5b9f221a761ed06ad5fd80c9b1f5ba02b97316
Took off this assertion that created problems
fixed a bug with fx_init
vlad321 (37):
Ticket #30. DHRectBound now no longer computes periodic distances, and that functinality has now been moved to DHRectPeriodicBound. This way users of periodic bounds can just call MaxDistance.
Just some quick formatting.
Fixes to bugs in the code
commit 08be73371a01ce25bbc23091db075b6a599157ba
commit b62901e13ec643ac98331430779e1b0f29736f21
Fixed DRange Contains so that it no longer returns true for any point.
commit 9b3a22376e50779ce9800e7689fc46a4319970fa
vim
commit 4acc47435fbd506cfcef95931906aa265fc1d84b
Fixed some backwards compatability issues.
Fix to the fix that broke a few tests.
Fixed some warning that were popping up.
Should actually work and no longer just fool the compiler to get it to build.
Fixed everything in PeriodicBound so that it works properly, and all memory problems have been fixed. However there are 3 Min and Max Distance function which seem to have logical problems still.
commit a5f2b99acf441aaa2ad5cbbd7b40827f40d24665
commit d3e8302c943f8b6553169c789eb2cf4cfb6d8162
Removed Dataset. Converted all data::Load and data::Save to armadillo's .load and .save.
The all encompasing test, it should be just names mlpack_test in the bit directory. All required dataset files are in a folder as well.
Cleaned up and moved all stray tests and test data that is included in the general mlpack_test.
Formatting for the entire /tests.
commit 0e39a07c249d1aebd3df401f0f5f854c229a8765
Turning in with some tests for the implemented distances in periodichrectbound.
Properly formatted /gmm
More test cases, as well as formatting of /kernel_pca
Correction for the range test.
Formatting of /kmeans.
The test cases for maximum periodic distance, as well as the code for both versions of the maximum periodic distance.
Removed the extra print statements that I forgot in there.
Formatting of /linear_regression
Formatted /mvu
Formatting of /radical
Formatted /pca
Formatted /nearest_neighbor
The fix to the previous fix.
Formatted /math
Formatted /util
Formatted /tree
wguan (7):
nnsvm1118
nnsvm0122
nnsvm-0123
nnsvm0122_deprecated_function_removed
nnsvm1124
nnsvm1124-2
nnsvm1124-3
yatin (1):
added q point vs r node prune
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