[scikit-learn] annotated tag debian/0.12.0-1 created (now 9d0df8f)
Andreas Tille
tille at debian.org
Wed Dec 28 13:10:58 UTC 2016
This is an automated email from the git hooks/post-receive script.
tille pushed a change to annotated tag debian/0.12.0-1
in repository scikit-learn.
at 9d0df8f (tag)
tagging b9ed384195df7b8d7824eac42f7b1bee58ef321c (commit)
replaces debian/0.11.0-2
tagged by Yaroslav Halchenko
on Thu Sep 6 21:38:10 2012 -0400
- Log -----------------------------------------------------------------
Debian release 0.12.0-1
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Alex Companioni (1):
Issue #339: minimizing number of calls in tests.test_hmm.
Alexandre Abraham (4):
Fix a bug in the ward clustering.
Add a non-regression test for the bug of connectivity fixing.
Put conversion after component computation
Fix test function name.
Alexandre Gramfort (57):
Merge pull request #851 from duckworthd/master
TST : tesitng intercept_ between dense and sparse
adding alexis to authors
typo
update tip on svm C param
Merge pull request #872 from jaquesgrobler/master
FIX : use RandomState rather than global seed
Merge pull request #881 from amueller/fix_ica_components_rename
FIX: fix buildbot ICA pb
Merge pull request #876 from alexis-mignon/master
FIX : fix a division by zero in LARS #63
Merge pull request #892 from ibayer/fix_mldata_docstring
FIX: C range in plot_cv_digits
Merge pull request #891 from ibayer/merge_cd
FIX : cleanup classes.rst + pep8 after merge of coordinate descent
Merge pull request #900 from kernc/neighbors_predict_proba
FIX : fix predict_proba in KNeighborsClassifier for old numpy
FIX: fix grid search when X is list #925
Merge pull request #932 from jaquesgrobler/master
Merge pull request #938 from ogrisel/svmlight-double-precision
Merge pull request #969 from jaquesgrobler/master
missing pl.show() in plot_digits_agglomeration.py
Merge pull request #983 from GaelVaroquaux/faster_ward
MISC : update my web site URL in what's new
ENH : MultiTaskLasso works (still draft)
FIX : fix docstring in MultiTaskLasso
ENH : add multi task lasso example
ENH + DOC : add MultiTaskElasticNet + doc + 1 example
update what's new
FIX : support 1d y in MultiTaskFoobar
rename ylabel in MultiTaskLasso example
moving MultiTaskLasso doc after E-net
FIX : remove unnecessary dgemm in cd_fast.pyx
FIX : catching pb with sparse input in MultiTaskElasticNet
FIX : make as_float_array keep fortran order on dense array when copy
ENH: simplify dict learning with gram and reg_param handling
ENH : add copy arg to array2d and new atleast2d_or_csr usual for sparse coordinate descent
ENH : add copy param to array2d_or_csx
ENH : add support for multitarget in sparse enet + simplify input checking
ENH : use multitarget in dict learning
FIX : fix tests
DOC : getting over docstrings
ENH : avoid a copy in MultiTaskElasticNet
add note on what's new
ENH : add support for sparse data in ElasticNetCV/LassoCV (not optimal)
ENH : use multitarget Lars and LassoLars in dict_learning
ENH : simplify handle of copy of Gram and X with array2d in OMP
style + typo
DOC : better reg_param docstring in dict learning
ENH : use build_dataset in multi target test
ENH : update warn for multitarget
update coef_path_ docstrings
use assert_true
API : consistent use alpha_/alphas_ for alpha/alphas estimated by CV in linear models (issue #1041)
DOC : add useful comment in code
addressing for round of reviews
DOC : better docstring for fit_path
Alexis Mignon (30):
Added positive constraints for the elastic net
Made the code pep friendly
Added fit_intercept for sparse ElasticNet as well as corresponding test
Corrected bad comment and the use of a typedef
Made code pep compliant
DOUBLE does'nt stand for a dtype
Added utility functions for csc sparse matrices
Modified: uses utility function for sparse csc matrices
Modified data generation so it can generate data adapted to positiveness constraints
Removed most python function calls
Removed duplicate definition of csc_mean_variance_axis0
Made the code pep8 compliant
Corrected doctring: CSR -> CSC
Regenerated with Cython
Corrected missing import of csc_mean_variance_axis0
Made code pep compliant
Modified: in 'center_data' makes a copy only when needed
Made code pep8 compliant
Unified access to 'mean_variance_axis0' for CSC and CSR matrices
Removed undeed functions
Added warm restart option and completed docstring
Completed docstrings, factorized some tests and added checks on dimensions
Added test case for warm_start
Added size check on coef_init
Made code pep8 friendly. Used random state with fixed seed.
Made code pep8 friendly.
Modified chi2 kernel approximation such that it deals with zero elements
kernel approximation: simplified mangement of non zero elements
For the sake of clarity, creates new temporary arrays instead of copying the same one several times.\n Modified error message for negative valued arrays.
pep8 compatibility
Andreas Mueller (270):
ENH normalized_mutual_information
Added mutual_info_score to the references
DOC narrative docs for normalized_mutual_info_score
DOC make formulars for clustering metrics more pleasing to the eye
ENH fix if entropy is zero in normalized_mutual_info_score
MISC extended example, fixed doc build warning
DOC made it more explicit that AMI is better than NMI
DOC typos (thanks @ogrisel) and some elaboration in docstring.
DOC added reference to Hila's thesis, added comment about equivalence.
ENH replaced v_measure_score computation with nmi computation.
DOC removed NMI from example plot as it is the same as V-measure
DOC comment on normalized mutual information
ENH simplified entropy calculation
Revert "DOC removed NMI from example plot as it is the same as V-measure"
Revert "Revert "DOC removed NMI from example plot as it is the same as V-measure""
Revert "ENH replaced v_measure_score computation with nmi computation."
DOC corrected relation of V-measure to normalized mutual information.
COSMIT typo in whatsnew
RELEASE HEAD is now 0.12-git
COSMIT pep8
MISC don't use fit parameters in example
ENH rename unmixing_matrix_ to components_ in FastICA
DOC document 'labels' argument of confusion_matrix
DOC fix see also in gmm
FIX made "unmixing_matrix_" a property as @larsmans suggested.
COSMIT pep8
ENH rename 'k' in KMeans and MiniBatchKMeans
ENH renamed 'k' to n_clusters in SpectralClustering
ENH rename k in clustering examples and doctests to n_clusters
ENH fixed ``n_cluster`` to ``n_clusters`` in examples. Thanks @agramfort
ENH check whether "k" was used in fit, not init, as GaelVaroquaux suggested.
Merge pull request #874 from temporaer/master
Merge pull request #858 from amueller/fastica_components_rename
COSMIT pep8
FIX typo in example. My bad.
FIX renamed what was `components_` to `sources_`
COSMIT rst error
COSMIT fixing doc building errors.
COSMIT typo
Merge pull request #776 from amueller/normalized_mutual_information
Merge pull request #868 from larsmans/liblinear-1.91
ENH "fit_pairwise" for spectral clustering.
ENH Starting on affinity propagation
DOC typo
DOC Improving docstring for SpectralClustering
ENH fixed affinity propagation test. Need more tests.
ENH fit_pairwise, transform_pairwise for KernelPCA
ENH base svm has fit_pairwise and predict_pairwise.
ENH fit_transform_pairwise for KernelPCA
ENH isomap uses new interface.
COSMIT get rid of debugging output
ENH GridSearchCV uses the new API
COSMIT forgot one print...
DOC Deprecation warning with removal version 0.13.
ENH going for a universal property ``_pairwise`` instead of many functions.
ENH Cleanup
FIX Fixing rebasing problems...
COSMIT avoid errors in tests.
ENH slight improvement to mds speed, modified examples to not run mds that long.
ENH added old confusion_matrix implementation as alternative for few labels.
Merge pull request #887 from danohuiginn/master
BUG fixing bug in entropy that I introduced, adding regression test.
FIX faces_decomposition example. That this broke only now is a sign of deep magic, better left unexplored.
Merge pull request #888 from jaquesgrobler/master
DOC removed irrelephant/confusion reference, added pointer to source (as there is no other possible reference).
DOC user guide pdf building. Kicked out a formular that rendered neither in html nor latex. Please don't hit me.
Merge pull request #889 from vene/generate-multitarget
Merge pull request #875 from AlexandreAbraham/ward_coo_bug
COSMIT pep8
MISC raise more helpful error message in GaussianProcess if optimization fails.
MISC added bigger "tiny" in lars_path. least_squares is float32.
MISC reduce code duplication, fix "self.gamma" modification
MISC A bit more cleaning up in BaseLibSVM
DOC added "fetch_mldata" to references.
CLEANUP remove linear_model.sparse.setup.py
COSMIT pep8
DOC rename lambda to alpha in plot_lasso_model_selection. Closes #903.
TESTING check that SVC checks the shape of precomputed kernels.
ENH Check that X is non_zero for MultinomialNB.
ENH fixed doctests, addressed comments.
DOC improve kmeans init doc.
Merge pull request #894 from amueller/svm_sparse_dense
FIX more doctests that I broke.
DOC comment in whats_new on changed behavior of ``gamma`` in SVM
Merge pull request #914 from alexis-mignon/master
Merge branch 'master' into fit_pairwise
MISC callable kernel gridsearch fix...
ENH factorize common tests.
ENH don't list abstract base classes
ENH make base classes abstract meta classes
ENH make all Estimators default constructible (except SparseCoder)
ENH Add MetaEstimatorMixin, make RFE default constructible
ENH make GMMs and LLE cloneable.
COSMIT get rid of warnings (can't get rid of deprecation warnings only :-/)
ENH make BaseLabelPropagation abstract base class, make OutlierDetectionMixin not inherit from ClassifierMixin
BUG fix testing for abstract classes
ENH default score func for univariate feature selection: f_classif
Make sparse svm base class ABC
FIX better class selection, more strict testing.
ENH more tests
MISC raise NotImplementedError instead of value error in decision_function of sparse SVM
ENH do zero mean, unit variance on iris, don't test naive Bayes (for the moment)
ENH change defaults on SGD (works on digits and iris and I just guessed them).
ENH avoid division by zero in LDA, also avoid reusing variable names.
MISC don't test SVM for the moment, rest works :)
ENH make LinearModel and LinearModelCV abstract base classes
ENH test regressors
MISC shuffle iris for SGD based methods
Revert "ENH change defaults on SGD (works on digits and iris and I just guessed them)."
ENH Fix seed that makes SGDClassifier work.
ENH create BaseRidge base class
ENH test more shapes, test non-consecutive classes, test accuracy on test set
FIX minor rebasing and other problems
MISC cleanup common testing
Merge pull request #893 from amueller/common_test
FIX for filtering of meta estimators in python2.6
ENH better input validation for prediction in SVC, LinearSVC.
DOC Also added some notes on my recent merge with tests and stuff to the whatsnew.
MISC fixed random seeds in LLE tests.
Merge branch 'master' of https://github.com/scikit-learn/scikit-learn
COSMIT pep8
COSMIT pep8
ENH in OvR, use constant predictor if one class always present or never.
MISC address Gael's and Lars's comments, make ECOC tests deterministic.
FIX trying to fix long-standing linker issue
COSMIT pep8
trying out some testing stuff
ENH put atlas checking in one place and load from there.
DOC typo / wrong parameter in lle docs
Improve test-coverage ;)
COSMIT some RST fixes for the docs
Remove empty statement
DOC doctest failed on my box because I had higher precision...
COSMIT typos in covertype benchmark
Merge branch 'master' of https://github.com/scikit-learn/scikit-learn
Merge pull request #886 from amueller/multiclass_always_present
COSMIT, removed scikits.learn things, removed orphan file.
ENH trying to catch that damn thing.
ENH better error messaged in multiclass as @mbondel suggested.
Merge pull request #1 from cournape/linking_arrayfuncs
ENH corrected errormessages for always present labels. ugh
FIX doctests for changed dtype
ENH fixed warning for output code
FIXed another doctest.
ENH add verbose warning about too little trees for oob. Should we catch the divison by zero warning for classification?
DOC made the pls example plots so much prettier
Merge branch 'master' into fit_pairwise
Fixed merge problem
ENH Removed stupid ``_pairwise`` property in BaseEstimator.
MISC minor cleanup in spectral clustering
FIX/TST test anc fix grid search with kernel pca and precomputed kernel in pipeline.
COSMIT comments not docstrings in tests
Merge branch 'master' into fit_pairwise
TST precision issue on my windows box :-/
ENH slight cleanup in LDA, QDA, support for arbitrary class labels.
ENH use LabelEncoder
COSMIT typo in pairwise docs
DOC added LabelEncoder to the References.
Merge pull request #1001 from serch/master
Merge pull request #1008 from mrjbq7/doc-fixes
COSMIT pep8
ENH just a little more input validation testing
DOC added default value of shrink_theshold to NearestCentroid docstring.
DOC added ``lowercase`` to CountVectorizer docstring.
FIX feature selection dies on non-csr sparse matrices (that are unsubscribable). Regression test should go in common testing.
DOC added class_weight to LogisticRegression docstring
ENH auc_score and average_precision_score. Closes issue #158.
ENH added to ``__init__.py`` and references.
DOC explained RFE default behavior in docstring.
MISC Added unconfigured windows box to mailmap. Sorry about that.
DOC add parameters to TfidfTransformer docstring
ENH slight cleanup in LDA, QDA, support for arbitrary class labels.
ENH use LabelEncoder
FIX Removed code-duplication introduced in rebase.
FIX Fixed variable names. Thanks @mblondel
DOC Added wikipedia references to docstrings
Merge pull request #1013 from amueller/auc_score
DOC Updated whatsnew
ENH sparse matrix support in univariate feature selection
TST Simplified tests, test that sparse and dense versions give the same result, always return arrays, not matrices.
DOC Polished some docstrings
ENH Added copy keyword to safe_sqr, added to dev docs.
COSMIT Fixed commata
ENH Addressed @mblondel's comments.
ENH simplify as @mblondel suggests
ENH sparse matrix support for RFE and RFECV. Closes issue #1018.
DOC updated whats_new
ENH going back to not using LabelEncoder.
Merge branch 'qda_lda_1000' of github.com:amueller/scikit-learn into qda_lda_1000
Merge pull request #1000 from amueller/qda_lda_1000
typo in linear_model doc
ENH add verbosity parameter to cross_validation_score
MISC catch warnings in covariance tests
Typo in last commit :-/ sry
ENH catch expected warning in ward clustering
ENH renamed ``min_n`` and ``max_n`` parameters in CountVectorizer to enable gridsearch over them together.
ENH renamed parameter bounds_n to ngram_range, fixed doctests and tests.
ENH addresses @ogrisel's comments
ENH fix merge with char_wb_ngram
ENH check that classifier decision_function and predict_proba validate shape of input.
Merge pull request #1046 from TimSC/master
COSMIT pep8
ENH rename paramter ``p`` of AffinitPropagation to ``preference``, slightly change the meaning of scalar parameter. Scaling the medium seems more intuitive that giving absolute values.
DOC fixed renaming of ngram_range in feature_extraction narrative
TST check that transformers fail gracefully on sparse input
ENH affinity propagation now has an ``affinity`` parameter, instead of a ``precomputed`` parameter, to support other affinities in the future.
ENH renamed ``gaussian`` affinity to ``rbf`` in spectral clustering for consistency.
COSMIT renamed n_points to n_samples everywhere, fixed shape docstring that @mblondel pointed out.
FIX Worst feature in RFECV missing. closes issue #681.
ENH renamed ``neq_sqr_euclidean`` to ``euclidean`` so we it is easier to parse
ENH Convert input into float in GMM
ENH add test, revert affinity propagation to previous parametrization (was a bit over-eager there)
TST added tests for different spectral clustering affinities
Merge branch 'fit_pairwise'
MISC add verbose keyword to AffinityPropagation
FIX fixed horrible bug in spectral clustering!!!!
ENH updated whatsnew for bugfix, removed warning box, tightened test.
TST classifier behavior with only one class present
ENH also test MultinomialNB
ENH some cleanup in grid_search.
Merge pull request #1068 from amueller/grid_search_cleanup
ENH add test for consistend predict_proba shape also in the two-class case.
tst add check for isotropic data in spectral clustering
FIX try to be a bit nicer to arpack - any one with a different setting care to try to make a more stable test?
FIX doctest corrected (hopefully this is deterministic) + cosmit
FIX removed isotropic spectral clustering test because of arpack problems.
FIX use backport of np.unique
FIX forgot some uniques
DOC fix minor sphinx errors and stuff
enh: try to get decision function to work in two class case
ENH make QDA and LDA decision functions adhere to standard shape [n_samples,] in two class case.
Fixed tests for RidgeClassifier
DOC updated whatsnew, moved @pprett's api fix into the api section.
ENH addressed @agramfort's comment, also removed the special case from testing as @mblondel fixed it :)
ENH added min_df keyword to CountVectorizer, default=2
ENH more robust testing for int
ENH more robust testing if parameter is int or float, as suggested by @larsmans in #1066.
FIX typo
COSMIT Typo. Englais svp. Closes #1090.
COSMIT trying to fix doc issues
DOC added min_df change to whatsnew, made more estimator names clickable.
ENH rudimentary testing of tranformer objects
MISC added comment to explain SelectKBest k in common tests
COSMIT copy+paste error
ENH test that regressors can handle integer data.
ENH add ClassifierMixin with ``fit_predict`` and some tests.
COSMIT remove commented out score
DOC CountVectorizerDocstring readability
DOC Added section on issue tracker tags to development docs
ENH raise ValueError in r2_score when given only a single sample.
ENH support custom kernels on sparse matrices
ENH added low-level bail out in sparse svm
MISC use assert instead of value error.
FIX add exception, check exception, if sparse.SVC is called with kernel='precomputed'
ENH fix error by removing unnecessary test.
DOC added some comments to the sparse precomputed kernel tests.
DOC updated whatsnew with ProbabilisticPCA fix by @kuantkid
Merge pull request #1109 from buma/predict_proba_doc
FIX affinity propagation typo
DOC fixed some sphinx errors, issues in docs....
COSMIT pep8
DOC fixed reference in whatsnew
DOC added some more API changes to whatsnew
FIX removed sparse_encode_parallel
COSMIT pep8
COSMIT typo, thanks @ogrisel
MISC changed version number for release, change maintainer to myself
DOC add people and commits do whatsnew
DOC added link to 0.11 docs to support page.
ENH more robust transformer testing.... don't ask why that came up
Brandyn A. White (1):
Faster confusion_matrix implementation
Brian Holt (3):
added multi-ouput tree example
updated documentation to reflect multi-output DT regression
added link
Bussonnier Matthias (1):
[Docstring Typo] making there -> making their
Charles-Pierre Astolfi (1):
Typo fix
Dan O'Huiginn (1):
Fix a few spelling/grammar errors in the docs
Daniel Duckworth (9):
Merged svm parameter selection visualization
split plot_rbf_parameters.py's plot into two
Added plot_rbf_parameters example to SVM doc
Fixed bug in plot_rbf_parameters.py causing only one figure to show
Fixed location of ".. _svm_mathematical_formulation:" in svm.rst
Convert input dtype to float in pairwise_distances
Convert input dtype to float in pairwise_distances
Merge remote-tracking branch 'upstream/master'
Python 2.6 bugfix for plot_rbf_parameters.py
David Cournapeau (1):
REF: hack to be able to share distutils utilities.
Edouard DUCHESNAY (3):
Some more non regression test on PLS
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Merge pull request #869 from pprett/pls-scale-by-zero
Fabian Pedregosa (9):
WEB: update the designer's URL
FIX: latex underscore
Explitit cmap for background.
Some doc for the example "Lasso path using LARS"
Some documentation for example plot_ridge_path
BUILD: add gemv cblas routine
BUILD: add dger cblas function
Update README.rst
Merge pull request #1078 from buguen/docs
Florian Hoenig (3):
added test that fails because Scaler.fit changes a sparse input vector when Scaler is initialized with copy=False
removed bug in Scaler.fit
improved test_scaler_without_copy
Francois Savard (2):
Fixed docstring for C param in BaseLibLinear/SVM subclasses.
Added version info to deprecation warning
Gael Varoquaux (89):
BUG: remove n_jobs=-1 from examples
Merge branch 'install-windows' of https://github.com/vene/scikit-learn
FIX: control RNG seeds in ICA tests
DOC: fix rst layout
MISC: clean up top-level namespace
P3K: more Py3k compat changes
BUG: multiple jobs in dict_learning
BUG: fix install bug for _check_build
BUG: casting error with recent numpys
DOC: note on heat kernel for spectral clustering
Typo
Typo
BUG: reassigning cluster centers with X sparse
BUG: k_means k -> n_clusters
COSMIT: k -> n_clusters
COSMIT: avoid deprecation warnings
MISC: os.name -> platform.system()
FIX: unique in old numpy
COSMIT in plot_mds.py example
DOC: misc improvements in MDS docs
DOC: minor MDS doc/example changes
MISC: update whats_new with MDS
BUG: address ill-conditionned designs in Lars
Cosmit: PEP8 :P
Cosmit: PEP8
COSMIT: intermediate variable
Merge pull request #953 from jaquesgrobler/nature_css_addons
ENH: backport gen_rst changes from NISL
ENH: minor speedup in Ward
ENH: factor 2 speedup in Ward
ENH: minor speed up in ward
ENH: minor speed up in Ward
Merge branch 'master' of github.com:scikit-learn/scikit-learn
MISC: avoid unprotected np.random
TST: testing without hard-coding the values
TST: test on diabetes rather than iris
Cosmit
BUG: example now needs 'assume_centered'
ENH: using slices rather than indice masks
ENH: avoid unecessary steps (covariance)
Cosmit: more explicit names
FIX: remove leftover print
Note on control of the RNG seed during testing
DOC: cosmit performance instructions
TST: test check_build
ENH: remove setuptools
ENH: restore 'develop' mode install
FIX: remove executable bit on joblib files
BUG: fix setup.py for develop
TST: test the setup.py using the configure step
MISC cleanup old coverage info in Makefile
ENH: Faster ward for large n_clusters
BUG: fix ward tests
DOC: ward docstring and testing
TEST: improve test coverage in hierarchical
FIX: make ward_tree work on 1D data
MISC: very minor speedup
COSMIT: remove left over profiling
TST: More testing in hierarchical
TST: test TypeError in Ward
TST: more tests for hierarchical
DOC: notes on improving code coverage
COSMIT: explainations of the partial import
MISC: build_utils: module rather than a subpackages
ENH: use sklearn.__version__ in setup.py
Merge branch 'linking_arrayfuncs'
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Cosmit: comment
TST: fix doctest
Update whats_new
Clean: remove debug print
PEP8
Typos
BUG: keep same shape for y in MultiTaskLasso
DOC: explicit MultiTaskLasso.coef_ dimensions
DOC: formatting and rephrasing in MultiTaskLasso
Merge pull request #1005 from NelleV/MDS
ENH: understandable error message for X sparse
BUG: casting rule with recent numpy
BUG: do not use diag_indices
BUG: choose seed to get affinity test working
BUG: fix my fix for affinity :(
DOC: link to Randomized sparsity in Lasso section
Merge branch 'master' into mixins
Revert "Rename Y to y in PLS"
Merge branch 'master' of github.com:scikit-learn/scikit-learn
BUG: sparse matrices in ElasticNetCV
MISC rest
DOC: improve scale_c_example
Gilles Louppe (94):
ENH: MultiOutputTree (wip)
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-mo
ENH: Multi-output decision trees
ENH: Regenerate .c file
FIX: graphviz test
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-mo
FIX: test_classification_toy
TEST: test_multioutput (1)
TEST: test_multioutput
ENH: make forests support multi-output
TEST: test_multioutput
ENH: Patch GradientBoosting
ENH: Patch GradientBoosting (2)
FIX: log_proba + DOC
DOC: What's new
PEP8
ENH: graphviz
DOC: narrative documentation
DOC: typo
DOC: Scikit-Learn -> scikit-learn
ENH: Cython improved code
ENH: Cython improved code (2)
DOC: narrative documentation
FIX: use and modify own y
COSMIT
FIX: segfault
DOC: Example
DOC: typo
DOC: example
DOC: typo
DOC: narrative documentation
DOC: docstrings for criteria
DOC: docstrings
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-mo
Merge pull request #3 from bdholt1/glouppe-tree-mo
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-mo
DOC: format
Merge pull request #923 from glouppe/tree-mo
Fix broken bot (sorry for that!)
Fix broken bot (again ;))
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-speedup
DOC: What's new > Missing links
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-speedup
Tree refactoring (1)
Tree refactoring (2)
Tree refactoring (3)
Tree refactoring (4)
Tree refactoring (5)
Tree refactoring (6)
Tree refactoring (7)
Tree refactoring (8)
Tree refactoring (9)
Tree refactoring (10)
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-speedup
Merge pull request #948 from mrjbq7/trees
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-speedup
Merge pull request #950 from mrjbq7/trees
Merge branch 'master' of github.com:scikit-learn/scikit-learn into tree-speedup
ENH: Tree properties
Tree refactoring (11)
ENH: make Tree picklable
Tree refactoring (12)
Tree refactoring (13)
FIX: avoid useless data conversion
FIX: avoid useless data conversion (2)
Tree refactoring (14)
Tree refactoring (15)
Tree refactoring (16)
FIX: @mrjbq7 comments
Tree refactoring (17)
Tree refactoring (18)
FIX: sample_mask
Merge branch 'tree-speedup' of github.com:glouppe/scikit-learn into tree-speedup
FIX: init/del => cinit/dealloc
Added _tree.pxd
FIX: gradient boosting (1)
COSMIT
Tree refactoring (19)
FIX: PyArray_ZEROS -> np.zeros?
FIX: gradient boosting (2)
Tree refactoring (20)
What's new
PEP8
Merge pull request #956 from Carreau/patch-1
COSMIT
Turn off warnings
FIX: test_feature_importances
FIX: test_feature_importances?
TEST: disable test_feature_importances for now
Merge pull request #946 from glouppe/tree-speedup
FIX: dtype conversion of y
EXAMPLE: plot importances with bars
FIX: forest / check_random_state in fit
FIX: tree / check_random_state in fit
Hannes Schulz (2):
MISC privatize/deprecate internal function of gaussian process
typo
Immanuel Bayer (33):
add dense attribute and dummy for sparse fit
Merge branch 'master' of https://github.com/scikit-learn/scikit-learn into merge_cd
add dense attribute and dummy for sparse fit
Merge branch 'merge_cd' of https://github.com/ibayer/scikit-learn into merge_cd
support of sparse input data added
tests of sparse coordinate_descent applied to the modified dense
-remove sparse option
remove sparse_coef_
Test is redundant since _set_coef function as been removed.
add property for sparse_coef_
add test for sparse_coef_ property
docstrings updated
merge cd_fast and cd_fast_sparse
remove redundant tests
remove redundant files, functionality has been moved to cd_fast.pyx
code removed and deprecated message added
fix docstring example
add test to check normalize option in sparse enet
Revert "remove redundant files, functionality has been moved to cd_fast.pyx"
Revert "remove redundant tests"
add sparse_std that has been wrongly removed in commit 48ba97f1 from the
update sparse_std call
some tests didn't use the numpy sparse matrix as input data and
make sure X is of dtype float64 in _sparse_fit
change input to inplace_csc_column_scale
modify test_normalize_option
test data changed for test_normalize_option
remove redundant folders in linear_model/sparse
remove unused imports
fix pip8
move sparse_center_data to linear_model.base
avoid copy if X has proper type, modify docstring
fix warning: add underscore to: grid_search.best_estimator_ and
Jake VanderPlas (5):
DOC: add tutorial links
TST: change LLE test to stable seed
DOC: fix documentation of arpack
Merge pull request #991 from jakevdp/doc-update
@jakevdp's version of pinvh
Jaques Grobler (37):
Added `note` to tutorial index for `doctest_mode` in `ipython`
Merge branch 'master' of https://github.com/scikit-learn/scikit-learn
changes to `fit` and `__init__`
decision logic removed from __init__
API update for HMM types with docstrings
tests updated to match API
fixed example`s fit(..) to new API
made `diag` explicit in example
Fixed typos, spacing errors & updated `Whats New`
fixed broken GaussianHMM documentation generation
correct some wrong fixes
reversed the order of the thresholds array
metrics.py
test added for this
fixed typos,updated `whats new`
typo fixed in what`s new
added alternating columns for tables in documentation and a tighter layout in pre
docstring fixes
Merge branch 'master' of https://github.com/scikit-learn/scikit-learn
Fixed broken links on Support page
Fixed broken links on Support page
Merge pull request #974 from jaquesgrobler/master
fixed long-name-references madness + removed some whitespace
trainling whitespace removed
blank line removed
slight adjustment to header size
Merge pull request #1075 from jaquesgrobler/master
Merge pull request #1077 from ludwigschwardt/minor-fixes
Added scale_c fiasco example
gael`s suggestions/tweaks
docstring change
docstring fixes
changed includes back - change broke JENKINS build
not the problem afterall - switch back
docstring changes
typos and alex`s review changes
small tweaks
John Benediktsson (8):
tree: check length of sample_mask and X_argsorted.
DOC: fix typos in tree docstrings.
DOC: fix value error text in Tree.compute_feature_importances.
COSMIT: Use np.array.fill for scalar values.
COSMIT: doc fixes to sklearn.feature_selection.univariate_selection.
COSMIT: fix typo of homoscedasticity.
COSMIT: fix reference to scipy.stats.kruskal.
COSMIT: fix more typos.
Keith Goodman (1):
BUG: price accidentally used instead of volume
Kernc (12):
KNeighborsClassifier now has a predict_proba() method
reversed changes to KNeighborsClassifier.predict()
an simple test case for KNeighborsClassifier.predict_proba()
feature_extraction.text.CountVectorizer analyzer 'char_nospace'
Oneliner docstring
words for n-grams padded with one space on each side
missing unicode modifier
replaced str.format() with string concatenation as it's 3 times faster
char_nspace -> char_nospace, thanks Lars
changed 'char_nospace' keyword to shorter and meaningful 'char_wb'
some narrative documentation...
mentioned 'char' vs 'char_wb' in the narrative
Lars Buitinck (45):
DOC clarify __check_build messages
DOC instruct new devs to *always* work in branches
COSMIT pyflakes + pep8 linear_model/base.py
ENH generalize LabelBinarizer to arbitrary Sequence types
BUG remove debugging statements from multiclass
BUG in LabelBinarizer (forgot to run the full testsuite)
DOC fixed sentence that was missing a verb
rm deprecated euclidian_distances synonym
ENH fix and test LabelBinarizer's handling of string labels
ENH import liblinear 1.91
COSMIT make a liblinear C private helper function static
BUG set new p parameter in liblinear helper
ENH support opening compressed files in SVMlight reader
ENH always support file descriptors in SVMlight loader
DOC typo in docstring
BUG do not close fd passed by user in SVMlight loader
FIX NearestCentroid.fit could not handle sparse formats other than CSR
DOC typo
DOC fix dead link
DOC + COSMIT additive chi² sampler
ENH scipy.sparse support in additive chi² sampler
DOC output from additive chi² sampler
COSMIT refactor input validation code and tests
COSMIT + DOC input handling and docstrings in RandomizedPCA
ENH classes_ on OvR classifier
DOC typos
COSMIT remove some dead code
BUG remove predict{_log,}_proba from SVR
COSMIT cleanup tests with pyflakes
ENH better input validation for dump_svmlight_file
ENH make generated SVMlight files self-describing in a comment
COSMIT don't call magic methods directly
ENH allow user-specified comment in SVMlight dumper
rm the long-deprecated scikits.learn package
TST: improve coverage of feature_selection.SelectorMixin
COSMIT suppress warning from qr_economic + docstring on Counter
TST absolute imports in spectral clustering tests
ENH more specific warning filter for qr_economic
TST upgrade trivial (single-class) k-NN problems to binary ones
DOC + TST vocabulary arg in CountVect docstring
COSMIT move BaseSGD to its only place of usage
COSMIT minor refactoring of SGD
DOC tutorial: explain what an estimator is
DOC rewrote logistic regression docs
DOC yet another AKA
Ludwig Schwardt (1):
FIX removed ancient templates from manifest to make sklearn pip-installable.
Marko Burjek (7):
DOC Added SGDCLassifier support only binary prediction probabilites.
DOC Fixed a return in predict_proba in SGDClassifier
DOC add support for sparse arrays to SGDCLassifer
DOC forgot dot in SGDCLassifier documentation
DOC Fixed a return in predict_proba in SGDClassifier
DOC add support for sparse arrays to SGDCLassifer
DOC forgot dot in SGDCLassifier documentation
Mathieu Blondel (60):
Rename "p" to "espilon".
Allow regression losses for classification.
Add epsilon-insensitive loss.
predict_proba with loss="modified_huber".
Update doc.
Doc: predict_proba.
What's new.
Document API change.
Easier to understand formula.
DOC LabelBinarizer
BUG: now build works.
Add LabelNormalizer.
Documentation for LabelBinarizer and LabelNormalizer.
Pep8.
Cosmit: LabelBinarizer and LabelNormalizer are not classifiers.
More useful error message.
Doc cosmit.
Add test for non-numerical labels.
LabelNormalizer -> LabelEncoder.
Add documentation for non-numerical label case.
What's new.
Cosmit: be more explicit why LabelEncoder is useful.
Address @larsmans' comments.
Merge branch 'sgd_losses' of github.com:mblondel/scikit-learn into sgd_losses
Address @ogrisel and @pprett's comments.
Fix remaining merge conflict.
Fix doctest.
Merge branch 'master' of github.com:scikit-learn/scikit-learn
What's new.
Fix typo.
Note regarding multilabel example.
Note on one-vs-all classification in SGD module.
Unused import.
Fix warning.
Merge pull request #877 from duckworthd/master
Fix #904.
Removed needless method redefinition.
Fix: RidgeClassifier must not inherit from RegressorMixin.
Clean up unused code.
Test default input.
Credits and license.
Update doc/whats_new.rst
Update doc/whats_new.rst
Typo.
Check that feature indices are sorted.
Add missing test file.
Optim in LabelEncoder.
Remove needless loop in inverse_transform.
Simplify LabelEncoder.fit_transform.
Fix warnings in multiclass module tests.
Remove duplicated line.
Add all_categories option.
Normalize training and test times.
Typo.
Simplify LabelEncoder.transform.
Test LabelEncoder.fit_transform with arbitrary labels.
Ignore joblib folder.
Fix #1080.
Decision threshold is now 0 in RidgeClassifier.
Optim + cosmit in StratifiedShuffleSplit.
Nelle Varoquaux (44):
Updated mailmap
Updated mailmap (bis)
Added Pool Adjancent Violator
SMACOF algorithm for MDS
Added tests and documentation to the smacof algorithm
PAV now uses Kruskal's first approach to ties
Added a new dataset: traveling distances between 17 cities in france
MDS now computes the SMACOF algorithm several times, and returns the results with the lowest stress
Added documentation on MDS
MDS can now run several jobs in parallel thanks to joblib - when initial array passed, MDS will also only run once. If n_init is not set to 1, it will raise a warning
FIX mds tests where failing because of an interface change
Added docstrings to MDS
Cleaned up MDS's documentation
Added more documentation on the cities dataset
Fix errors due to previous refactoring on MDS
Changed dataset from france's mileage to knuth's USA mileage dataset
Replaced MDS US mileage distance example by a generated, more representative one
Added paragraphs on metric and nonmetric MDS, explaining the difference
MDS: out_dim → n_components
MDS: added documentation for n_jobs parameter
MDS - fixed some latex error in the documentation
Added a fit_transform method to the MDS class
Pool Adjacent Violators now does a max_iter number of iteration
DOC: added references to papers and licence - fixed the MDS example
a += a.T is different from a = a + a.T
Small explanation on the plot_mds example
np.diag raised a red flag - used broadcasting instead
Set the seed of the random_state generators to have nicely aligned results
Knuth load_cities dataset isn't used anymore
MDS: renamed positions_ to embedding_
Added MDS to manifold comparison methods
MDS: documentation fixes
FIX: load_cities doesn't exist anymore
Added test to sklearn.utils.bench's total_seconds method
FIX - the eps option of the MDS was overwritten
FIX in the makefile - we should delete pyc and so only from the source code, and not from everything in the root folder
Deprecated sparse classes from the SVM module - refs #1093
FIX sparse OneClassSVM was using the wrong parameter
FIX the AP was using a deprecated parameter
Decrease the number of convit in the AP
Renamed parameter convit to convergence_iteration and deprecated the old API
FIX typo in deprecation warning in the AP module
DOC better documentation on the AP
FIX The new parameter of the AP is called convergence_iter and not convergence_iteration anymore
Nicolas Pinto (5):
ENH: add store_loo_values attribute to _RidgeGCV see Issue #957
FIX: expose loo_values_ in RidgeCV instead of the private _RidgeGCV
COSMIT: rename M matrix to loo_values
COSMIT: -loo_values +cv_values
FIX: use rng with fixed seed
Olivier Grisel (27):
trailing space
add missing attribute estimators_ to the docstring of forest models
FIX #898: narrative documentation for feature importances in forest models
Merge pull request #921 from fhoeni/scaler_bugfix
FIX: heisentest for robust covariance: seed MinCovDet
Merge pull request #926 from agramfort/fix_X_list_grid_search
Merge pull request #928 from yarikoptic/master
FIX #937: preserve double precision values in svmlight serializer
add a what's new entry
work on smmlight serualizaer to preserve double precision values
track master
Merge pull request #945 from cpa/master
Merge pull request #971 from acompa/master
Update doc/support.rst
Merge pull request #955 from vene/mem_prof
Merge pull request #995 from kernc/CountVectorizer_analyzer_char_nospace
fix broken doctests for the new char_wb text analyzer
DOC: better narrative for char_wb text analyzer + add a whats_new entry
Merge pull request #1043 from jaquesgrobler/master
Merge pull request #1039 from jakevdp/lle-test-fix
Merge pull request #1045 from agramfort/fix/as_float_array
Merge pull request #1049 from fsav/c-docstring-patch
Merge pull request #1063 from welinder/peter-dev
Merge pull request #1009 from amueller/one_class_check
Merge pull request #1094 from ibayer/warnings
Merge pull request #1100 from NelleV/makefile
Merge pull request #1110 from buma/predict_proba_doc
Olivier Hervieu (1):
FIX inconsistent coef_.shape in LinearRegression
Peter Prettenhofer (79):
fix: gradient boosting regressor does not check if X is c-continous
Merge remote branch 'upstream/master'
started work on Huber loss function for robust regression
ensure that std is not zero
add test case for scale div through zero
Merge branch 'master' into gbrt-huber
add huber loss to test
implemented huber loss for robust regression
fix errors in huber loss
add alpha parameter for huber robust regression loss
fix: ensure X is c-continuous
fix: make sure X is c-continuous
Merge branch 'master' into gbrt-huber
added feature subsampling to GBRT (via max_features)
fix: forgot comma
added test for max_features
fix: alpha needs to be scaled by 100
wip: added quantile regression loss; this allows for prediction intervals; adopted the GP regression example to show-case prediction intervals
added title to example
performance improvement for random split (ctyped two variables).
import random split
test for quantile loss function
Use BaseEstimator for constant predictors
cosmit
huber and quantile loss for gbrt
better docs for quantile reg
Merge branch 'master' into gbrt-huber
Merge remote branch 'upstream/master' into gbrt-huber
ctyped variables in ``find_random_split`` and use for loop over index range instead of array elements
Merge branch 'master' into gbrt-huber
fix: np.arange dtype issue; fix dtype to be np.int32
use np.int32_t instead of Py_ssize_t
Merge branch 'master' into gbrt-huber
Merge remote branch 'upstream/master' into gbrt-huber
use dtype float32
proper pylab import
Merge branch 'master' into gbrt-huber
Merge remote branch 'upstream/master' into gbrt-huber
added test case for symbol labels
y must be one dimensional
more tests
removed quantile regression example
added max_features to gbrt regularization example
fix: section label for gbrt was wrong
add quantile example again
added new features to whatsnew
Merge branch 'gbrt-huber'
change dtype of y to float64 (aka DOUBLE_t)
cosmit: better docstrings
forest uses DOUBLE for y
Merge branch 'master' into tree-y-float64
changed shape of predict_proba
adopted tests because of changed shape of predict_proba
adopted tests because of changed shape of predict_proba
cosmit in sgd docs
added change to ``whats_new``
add quantile regression example to gbm doc
Merge branch 'master' into sgd-predict-proba
Merge branch 'sgd-predict-proba'
added failing test for 2d y
rm redundant input check (we check in _partial_fit)
ravel y; use atleast2d_or_csr for input validation
_tocsr not needed because of atleast2d_or_csr
inline comment
cosmit: constants for penalty types and learning rate types; inline comments;
Merge branch 'master' into sgd-yshape-fix
fix typo
make smoke tests explicit; check ValueError on 2d inputs
work on BaseGradientBoostingCV
refactored prediction and decision_function (rm duplicate code)
ENH: use gini for feature importance
GradientBoosting classes with built in cross-validation; implemented via Decorator pattern
wip: aggregate fold via groupby
wip: fixing some set attr errors but still buggy if params not lists
remove *CV classes - only pick decision_function and staged predict refactoring
rm CV class tests
rm CV class legacy
remove CV class legacy
add API changes and feature_importance fix to whatsnew
Peter Welinder (2):
add support for non-ndarray lists
Merge branch 'master' into peter-dev
Robert Layton (9):
This test repeats issues 960, with the silhouette coefficient returning nan
nan values are converted to zeros
k-means now no longer needed in test.
Distance matrix doesn't matter, and was therefore removed
Test for "amg" mode for spectral clustering added.
docfix: spectral_cluster doesn't return n_centers
pep8
Spectral will raise an error if the mode is set to amg and pyamg is not available
Test that an unknown mode raises the appropritate error
Sergio Medina (1):
Fixed small typo, even though the message is kind of the same and the one with the typo is waaay funnier.
Shiqiao Du (1):
Merge pull request #847 from kwgoodman/master
Subhodeep Moitra (16):
P3K: 'type' has been renamed 'class' in python3
P3K: Fixed dtype doctests for Python3
P3K: Fixed print related Python3 errors
P3K : Fixed range iterator to be list
PK3: __len__ returned float instead of int. Typecasted.
P3K : Convert int type checking to np.integer
P3K : Typecasted float to int
P3K : Changed / to // to typecast float to int
P3K: Modified RuntimeError message args
P3K : Replaced / by //
P3K : Refactored test cases to use setUp
P3K: print back compatible with python2.6-7 with __future__ import
P3K: Fixed None < Float Python 3 error
P3K: Fixed unicode pickling error by changing to BytesIO
P3K: Fixing prints and dtypes
P3K: Fixed RuntimeError.message
Tim Sheerman-Chase (1):
Enable graphvis export function to export trees as well as regressors
Virgile Fritsch (12):
rename mahalanobis_values to raw_values in covariance decision method.
ENH: make LedoitWolf estimation scale (memory usage) with n_features.
The LedoitWolf object has to return a covariance estimate or breaks.
Put Ledoit-Wolf shrinkage coefficient estimation in a separate function.
Avoid extra computations + clean `assume_centered` argument use.
Remove forgotten line related to previous commit.
Catch non-invertibility errors within MinCovDet computation.
Improve covariance module test coverage.
More tests for the covariance module.
BF: adapt a svm test to recent numpy versions.
BF: Make MinCovDet work with n_samples >> n_features.
Add comments on optimized precision computations.
Vlad Niculae (57):
DOC: updated testing instructions
Remove a warning from kmeans tests
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Remove deprecation warning in sparse_encode
Merge pull request #873 from vene/remove_sc_warning
ENH: make_regression supports multiple targets
Update make_regression return shapes in docstring
FIX: sparse ElasticNet tests that were not testing much at all
fix typo
ENH: faster design in FastICA
Begin updating the developers performance documentation
Update and fix errors in memory profiling documentation
DOC: better phrasing about memory profiling
Begin updating the developers performance documentation
Update and fix errors in memory profiling documentation
DOC: better phrasing about memory profiling
Remove deprecated _set_params and the call in grid_search
Remove chunk_size from k_means
Removed load_filenames and load_20newsgroups
Remove sparse_encode_parallel
Removed deprecated parameters in GridSearchCV
Remove LARS and LassoLARS
Remove fast_svd.
Remove _get_params
Corrected deprecation schedule in cross_validation
Remove deprecated properties in naive_bayes
Add or fix deprecation schedule in warnings.
Fix example using deprecated API, output was misleading.
Remove deprecated load_20newsgroups from classes.rst
FIX: randomly failing CountVectorizer test
MDS is not a transformer, fix the test to skip PLS
Merge branch 'master' into mixins
Improve the common tests, make fast_ica pipelinable
Support y-dependent transform as in PLS
fit_transform in PLS to support y
Make PLS degrade gracefully on sparse data
Rename Y to y in PLS
Check for sparse input in isomap and lle
Check for sparse data in MDS despite not being tested
Skip CCA in test_regressors_int
First effort in multitarget lassolars
ENH: move Gram precomputation outside of the loop
TEST: precomputed lasso and lars
Unnecessary copying
FIX: add test, fix memory initialization bug
ENH: multidimensional y in ElasticNet (WIP)
return_path option in lars_path
Add possibility to ignore the path in Lars objects
Fix doctests
Add __all__ for half of the scikit
Add __all__ for the second half of the scikit
Expose ENGLISH_STOP_WORDS
We already have the inverse at that step
Compute pseudoinverse using eigendecomposition
Vectorize singular value inversion
Cloned @jakevdp's pinvh tests
Use pinvh wherever it helps in the codebase.
Wei Li (2):
FIX: this fixes issues #746 ProbabilisticPCA minor things
FIX: this further fixes issues #746 with API compatibility warning and integer division fix
Yannick Schwartz (13):
New stratified shuffle split version that only return indices arrays
stratified shuffle split can return masks
Fixed StratifiedShuffleSplit issue for unbalanced classes
Fixed n_test issue in StratifiedShuffleSplit
pep8 fix
Added new tests for StratifiedShuffleSplit
Fixed SSS test
Removed redefinition of variable i in SSS
Permute the train and test sets in SSS to avoid class-sorted folds
Added validation for some corner cases in SSS
Updated tests for SSS
Added tests for the StratifiedShuffleSplit to check the sizes of the training and testing sets, and that they don't overlap
Minor cleanup of StratifiedShuffleSplit
Yaroslav Halchenko (11):
ENH do not fail the test reslying on numpy div 0 warnings if those are not spit out by numpy in general
ENH: sklearn.setup_module to preseed RNGs to reproduce failures
Merge tag '0.12' into releases
Merge branch 'releases' into dfsg
Merge branch 'dfsg' into debian
changelog for fresh upstrem release: all debian/up_ patches removed, deb_ patched updated
Boosted policy to 3.9.3 (should be ok without changes)
patches/deb_disable_test_spectral_old_scipy - disable unittest on older scipy's due to failure
updated copyright years and added owner for borrowed ATL_* code
fixed typo
removed obsolete (and not used any longer) python-psyco from Recommends
buguen (1):
correcting typos in the doc
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