[scikit-learn] annotated tag debian/0.14_a1+git20-gc9ba2c3-1 created (now 7946ba8)

Andreas Tille tille at debian.org
Wed Dec 28 13:11:03 UTC 2016


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tille pushed a change to annotated tag debian/0.14_a1+git20-gc9ba2c3-1
in repository scikit-learn.

        at  7946ba8   (tag)
   tagging  7c6e398d5a05caa7ab61bfad0c4bdf03482a1c4e (commit)
  replaces  debian/0.13.1-1
 tagged by  Yaroslav Halchenko
        on  Tue Aug 6 23:05:20 2013 -0400

- Log -----------------------------------------------------------------
scikit-learn Debian release 0.14~a1+git20-gc9ba2c3-1
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A. Flaxman (3):
      DOC: add random_state parameter to StratifiedShuffleSplit doc string
      DOC: latex beautification
      DOC: latex beautification

Abhijeet Kolhe (1):
      Fix setup.py to resolve numpy requirement

Alexander Fabisch (1):
      DOC update example path

Alexandre Gramfort (64):
      ENH : add reconstruction_err_ for NMF with sparse input
      use scipy.linalg in test_nmf.py
      adding comment on why sparse frobenius is ok as done
      Merge pull request #1607 from agramfort/reconstruction_err_nmf_sparse
      FIX : fix kfold balance due to int rounding
      FIX : test due to KFold change
      FIX : better fix of KFold balance
      fix doctest
      TST : improve test_kfold_balance test
      update what's new
      TST : improve again  test_kfold_balance test
      Merge pull request #1772 from jnothman/comment_exhaustive_search
      typo
      pep8
      Merge pull request #1907 from aflaxman/stratified_shuffle_split_rand_state_doc_str
      Merge pull request #2071 from djv/patch-1
      Merge pull request #2075 from jnothman/agglomeration_simplify
      FIX : use unique from fixes
      Merge pull request #2074 from jnothman/ward_docstring
      Merge pull request #2080 from ahojnnes/dist-todo
      FIX : missing y=None in FactorAnalysis
      Merge pull request #2087 from ahojnnes/examples-print-doc
      Merge pull request #2118 from NelleV/DOC_fix
      Merge pull request #2135 from fhs/meanshift-doc
      Merge pull request #2138 from NelleV/kCCA
      Merge pull request #2142 from sergeyf/master
      Merge pull request #2145 from NelleV/kCCA
      FIX : finish get rid of fit_... param
      ENH : avoid one copy in FastICA code
      misc
      update ICA examples
      adding comment
      Merge pull request #2196 from erg/labelencoder-docs-fix
      ENH : massive refactoring of CV models in coordinate descent. Now the algo core is in path functions
      update what's new
      DOC : more fixes in covariance module
      Merge pull request #2202 from NelleV/isotonic_reverse
      Merge pull request #6 from jaquesgrobler/cov_doc_fix
      Merge pull request #2203 from agramfort/cov_doc_fix
      cosmit : protect attributes in RBM for sphinx
      pep8
      better coverage
      fix doctest
      ENH : use warning instead of print
      update what's new
      Merge pull request #2212 from dengemann/ica_memory
      Merge pull request #2213 from cmd-ntrf/master
      Merge pull request #2217 from vene/ica_fit_transform
      Merge pull request #2182 from NelleV/pls_refactor_2
      DOC+ENH: fixes in least_angle + one vectorization
      DOC : better doc of array shapes in fastica
      MISC : use linalg from scipy
      ENH : removing warnings from tests in cd linear models
      Merge pull request #2194 from NicolasTr/as_float_array_copy
      Merge pull request #2223 from arjoly/doc-datasets
      DOC : docstring fixes
      DOC : more docstring fixes
      use pre_fit in OMP
      API : deprecate a lot of extra parameters in OMP object
      API : deprecations in orthogonal_mp
      ENH : update example of OMP
      update what's new + classes.rst
      Merge pull request #2247 from pgervais/docfixes
      Merge pull request #2258 from NicolasTr/ignore_pycharm_files

Andreas Mueller (186):
      REL change version to 0.14-git everywhere, update news, support page.
      website: fix for survey bar
      COSMIT remove unused imports, pep8
      TST some more tests for multi output lars
      DOC fix typo in LinearSVC error message
      FIX make error message work when return_path=False. Btw I feel that getting "references" for numbers out of numpy arrays is pretty ugly.
      TST fix random states in all dict learning tests, make test independent of test sequence.
      Revert "trying travis cfg with system-site-packages"
      COSMIT pep8
      DOC add return values of cross_val_score and train_test_split to docstrings.
      ENH added test, started on cross_val_score
      ENH adding SomeScore objects for better (?!) grid search interface.
      ENH refactor, taking @GaelVaroquaux's and @ogrisel's suggestions into account
      ENH deprecated ``score_func``, introduced ``score`` parameter in GridSearchCV
      TST test giving score as string in GridSearchCV
      FIX rename ``score`` to ``scoring`` because of the name-clash with the ``score`` function.
      FIX two score objects, adjust tests to new interface
      ENH remove old interface completely from tests.
      DOC fix docstring
      ENH working on cross_val_score, trying to simplify unsupervised treatment.
      ENH better testing of old an new interface. Still a bit to do for unsupervised grid search, though.
      FIX usage of scores for unsupervised algorithms.
      ENH use new api in permutation_test_score, don't use old api in testing.
      ENH fbeta score working, more tests
      DOC-string for AsScorer
      ENH renamed ap and auc, added RecallScorrer
      DOC narrative docs for scoring functions. Put them next to GridSearchCV. Should they go into metrics?
      ENH update example, minor fix.
      DOC improve cross validation and grid search docstring
      FIX rename error
      DOC add whatsnew entry
      DOC fixed formatting in user guide
      FIX example
      DOC added a new template to sphinx so view the "__call__" function.
      COSMIT address @ogrisel's comment.
      FIX rename ZeroOneScorer to AccuracyScorer
      DOCFIX for zero_one_score / accuracy_score renaming
      DOC add narrative about score func objects to the model_evaluation docs.
      ENH rename scorer objects to lowercase as they are instances, not classes
      DOC minor fixes in pairwise docs.
      ENH/DOC add "score_objects" function for documenting the score object dict.
      DOC add metrics.score_objects to the references
      DOC use table from score_functions docstring in model_evaulation narrative.
      DOC move scoring function narrative above dummy estimators, fix tables, some refinement.
      DOC minor fixes in score_objects documentation.
      DOC better table of score functions in grid-search docs.
      ENH GridSearchCV and cross_val_score check whether the returned score is actually a number, not an array (otherwise cross_val_score returns bogus).
      TST improve coverage of permutation test scores
      TST slightly better test coverage in cross_val_score
      COSMIT built-in typo
      DOC some improvements as suggested by @ogrisel
      TST add test for pickling custom scorer objects
      DOC more improvements by @ogrisel
      COSMIT rename AsScorer to Scorer
      MISC moved score_objects.py to scorer.py, added module level doc string and license note.
      DOC add kwargs in Scorer to docstring.
      ENH add ``__repr__`` to Scorer
      DOC addressed @ogrisel's comments.
      COSMIT text reflow
      MISC pep8: rename scorers to SCORERS, remove score_objects getter
      DOC remove duplicate table, add references to appropriate user guide section to docstrings of cross_val_score, GridSearchCV and permutation_test_score
      DOC add note on deprecation of score_func to whatsnew
      FIX imports for Scorer and SCORERS
      DOC fixes in whatsnew, typo
      TST smoke test repr
      COSMIT removed unused imports, fixed error message in test of boosting
      ENH break ties in OvO using scores
      TST test for breaking OVO ties
      COSMIT pep8
      ENH get rid of imports in test_common by checking by names, not classes.
      ENH fix test_estimators_overwrite_params to also test regressors and transformers. Then fix all the regressors and transformers ... meh!
      ENH set the random state to avoid heisenfailures
      COSMIT pep8, removing unused imports
      FIX remove dtype from covertype, add fetch_covtype to init, add missing docstrings.
      FIX doctest kernelpca
      ENH get rid of most imports in test_common
      TST stronger tests for arbitrary classes. make explicit what works and what doesn't.
      FIX rebasing trouble in common tests: the meaning of dont_test changed
      FIX don't compare strings with "is". that is really not robust!
      ENH in transformer pickle test, only test transformers that provide a 'transform' method. and only test that.
      ENH in common tests, use long variable names for all tests
      FIX remove all unseeded random variables from common tests.
      Merge pull request #1695 from mrjbq7/issue-1694
      COSMIT pep8: blank line contains whitespace
      DOC added sentence about oob_decision_function_ containing NaN to docstring. Still need some narrative about oob score.
      DOC add 0.13.1 changelog to whats_new.rst
      DOC add random_state parameter to docs of LogisticRegression and LinearSVC
      TST/FIX set random_state in logistic regression tests
      TST/FIX always use "almost equal" for floats.
      FIX MinMaxScaler bug.
      TST FIX random state for LibLinear sparse tests
      ENH add randomized hyperparameter optimization
      DOC fixed links in whatsnew
      Merge pull request #1736 from jamestwebber/patch-1
      Merge pull request #1740 from tjanez/move_roc_curve_test
      COSMIT pep8
      DOC FIX links on grid search narrative
      FIX compute_class_weight edge case
      DOC some sphinx / rst fixes
      MISC minor fixes in examples
      DOC FIX column span alignment problem in NMF ^^
      COSMIT typo
      DOC fixing some more rst / sphinx errors :-/
      DOC more sphinx stuff.
      Merge pull request #1767 from rmcgibbo/balltree_docstring
      DOC add roll your own estimator docs
      FIX for iid weighting in grid-search
      DOC FIX finite precision
      COSMIT pep8
      DOC correct / simplify dbscan examle
      COSMIT typo. the French again ;)
      FIX setting k in KMeans and MiniBatchKMeans was silently ignored. Left over in 07c56d7cd2ddfe71e7a4399d74fc367d6000d854 Damn, that was nasty :-/
      COSMIT pep8
      FIX jenkins error on numpy 1.3.0
      DOC documented n_init parameter of MiniBatchKMeans. Closes #1900.
      FIX broken scorer, add non-regression test.
      FIX WARN about **params being not used in GridSearchCV.fit. Closes #1815.
      FIX bug in callable kernel decision function - Sorry, I think that was me.
      FIX test error in test common for KernelPCA that doesn't respect its n_components.
      FIX typo in test for RdigeCV
      DOC typo in RandomizedSearchCV docstring
      DOC fetch_20newsgroups returns the text, not text files. see SO question: http://stackoverflow.com/questions/16615523/using-scikits-kmeans-to-cluster-ones-own-documents
      DOC Fixed documentation of kernel parameters: sigm uses gamma, but not degree. Closes #1972.
      DOC clarification in Scoring objects: Its not a good sign if I don't understand my own wording.
      DOC much more readable formula in chi2 kernel doc
      COSMIT sphinx fixes
      COSMIT pep8
      DOC FIX typo on fbeta, closes #2219
      fix whitespace around new tree.pyx docstring
      use new virtualenv features of travis, so we don't have to kill the virtualenv
      FIX hopefully fixing travis.
      FIX hopefully fixing travis.
      DOC improve svm sample weight example
      DOC improve documentation of sample_weight, add to docstring.
      TST small improvement of test for sample weight in svm
      cosmit typo
      Show 95% confidence interval, not 40% confidence ^^
      FIX whoops sorry!
      fix pycharm file ending
      ENH add "make_y_1d" to utils, use it in estimators where needed.
      fix make ``make_y_1d`` save for lists.
      use column_or_1d, move it to utils
      ENH rename eval / pseudolikelihood to score_samples
      fixing ridge and label binarizer... I'm pretty sure that worked before?
      FIX make neighbors y prediction shape consistent
      TST add regression test for label_binarizer
      FIX/ENH make StandardScaler convert int input to float and warn about it, instead of warning and rounding for dense and crashing for sparse.
      DOC adjust docstring as suggested by @gvaroquaux
      addressing @ogrisel's comments: catch warnings in test, no unneeded digits
      COSMIT fixing some unused imports, adding stuff to __all__,  and light pep8 (not all whitespace to make rebasing less painful)
      DOC fixing some sphinx stuff.
      more sphinx fixes
      first try at bootstrap-based website
      "fix" sidebar stuff - this was not my idea
      remove gray boxes around h3 on the two new pages
      put banner into header, make it spread over whole page
      Fix link to flowchart, add text descriptions.
      Minor fixes in front-page text, css
      rework front-page box texts
      fix typo, missing p
      fix and refine some css and html tags
      add example banner image
      add section, estimator and model links on the frontpage
      fix styling of rst links
      add links for examples
      fix css that I just broke with the sphinx links
      flatten the tutorial / doc structure as proposed by @ogrisel
      add js for collabsible toc tree in the user guide.
      minor typo thing
      don't have old version warning on install, as that will be shared across all versions.
      added "show source" link to footer, made dimensionality reduction examples link to decomposition
      slightly hackish way of inserting a whatsnew link. I really don't want all the sphinx containers here, though. Asked on stackoverflow about it btw.
      a little less ugly footer. @glouppe should maybe have a look ;)
      make links to old versions actually do something (currently link to the user guide as the other versions are not rebuild yet).
      replaced lorem ipsum in news. still a draft but whatever.
      nicer dates
      Try to raise and test warnings.
      DOC added website to whatsnew, added link to github for Nelle
      FIX don't use old API in examples
      more fixes for docs, deprecated interfaces
      FIX made the building of the docs slightly more robust. readme files in folders without examples kill it otherwise.
      try to fix the toctree in a semi-meaningful way.
      DOC/EXAMPLES fix more documentation errors, deprecated api usages.
      EXAMPLES remove non-existing example from doc, don't trigger deprecated interface in enet_path, lasso_path
      much better input validation, test that warning is raised on (n_samples, 1) y
      rearrange permutation_score parameters to match previous ones.

Arnaud Joly (121):
      Typo
      ENH multilabel metrics: accuracy, Hamming, 0-1 loss
      DOC FIX foating point issue
      FIX numpy 1.3 issues with multilabel metrics
      ENH add normalize option to accuracy_score + FIX bug with 1d array
      DOC return_path argument, prettier references
      ENH more pythonic way to treat list of list of labels
      ENH add jaccard similarity score metrics
      FIX compatibility issue with np 1.3 py 2.6
      ENH add multilabel support to PRF metric family
      ENH remove pos_label argument with multilabel binary indicator format
      ENH remove warnings at testing time
      FIX unique_labels in corner case
      FIX issue with comparable but different dtype
      ENH don't allow mix of input multilabel format
      ENH simpler check for mix of string and number input
      COSMIT better name
      Typo
      ENH use type_of_target within unique_labels
      ENH improve documentation with allowed label types
      ENH check that we don't mix number and strings
      Flatten label type checking
      TST add smoke test for all supported format
      COSMIT
      PY3K use six.string_type
      OPTIM + ENH simplify mix string and number check
      FIX bug with indicator format
      ENH use a comprehension over imap
      @arjoly and @glouppe thanks their funding FNRS and DYSCO
      ENH remove _is_1d and _check_1d_array thanks to @GaelVaroquaux
      flake8
      ENH raise ValueError with row vector if multilabel or multioutput is not supported
      ENH being less permissive thanks to @jnothman
      DOC add example is_multilabel
      ENH handle properly row vector
      Flake8
      ENH better error message
      FIX switch to the new format syntax
      ENH prettier error message for _binary_clf_curve with bad input shape
      ENH use ravel instead of atleast_1d and squeeze whenever possible
      ENH coherently input checking for regression metrics
      ENH dryer thanks to @jnothman
      TST stronger test for _column_or_1d function
      FIX ^ is a symetric difference
      MAINT Set random_state, modernize tests
      TST max_features for more tree estimators
      TST remove unused tests
      ENH add missing pxd of utis.random
      ENH Use file configuration
      FIX signature
      TST error message for _check_clf_target
      COSMIT
      FIX TST given cosmit
      COSMIT don't need set
      DOC explain the code
      COSMIT product(..., repeat=2)
      Update mailmap
      DOC add missing datasets helper
      ENH remove deprecated
      ENH remove deprecated things (2)
      Update what's thanks @NicolasTr
      ENH add support for string input with classification metrics
      ENH use the new format syntax
      ENH remove inspect
      COSMIT
      Update what's new
      DOC state that string is possible
      TST with labels arguments
      FIX what's new...
      ENH remove bad examples
      DOC let some example for prf metrics
      ENH allows make_multilabel_classification to return label indicator f…
      TST grid_search_cv works with multioutput data
      TST cross_val_score with multoutput data
      COSMIT
      ENH consistency mse=> mean_squared_error ari => adjusted_rand_score
      FIX docstring
      Update what's new
      DOC add missing links to the scorer and classication section
      ENH add multioutput support to KNeighborsRegressor
      ENH add multioutput support to RadiusNeighborsRegressor
      ENH add multioutput support for KNeighborsClassifier
      ENH add multioutput support to RadiusNeighborsClassifier
      DOC + example with multioutput regression face completion for knn
      ENH allows make_multilabel_classification to return label indicator format
      ENH TST grid search with multioutput
      ENH TST random search with multioutput data
      DOC gridsearch support mulioutput data
      TST cross_val_score with multioutput data
      DOC more information about which classifier support multilabel
      DOC unveil that some estimators support multilabel classification and multioutput-multiclass classification
      DOC overall improvements
      pep8
      DOC credit + fix typo + wording + use mathplotlib.pyplot
      ENH take @glouppe comments into account
      FIX small title issue
      DOC update what's knn and radius-nn support multioutput data
      FIX bug in f_score with beta !=1
      FIX formula inversion for sample-based precision/recall
      FIX set same default behavior for precision, recall and f-score
      ENH raise warning with ill define precision, recall and fscore
      Backport assert_warns and assert_no_warnings from np 1.7
      TST test warning + ENH Add warning average=samples
      FIX TST with warnings thx to @jnothman
      flake8
      ENH set warning to stacklevel 2
      TST silence warning
      ENH use with np.errstate
      DOC TST correct comment
      FIX warning test
      FIX warning tests in preprocessing
      PY3K remove __pycache__ in make clean
      FIX PY3K warning.catch_filter set record
      DOC overall improvements in the multiclass documentation
      DOC take into account @vene and @ogrisel + specify format for multioutput-multiclass
      DOC rewording
      Typo
      DOC ENH take into account @NelleV comments
      DOC more comments from @NelleV
      DOC Remove deprecated reference + acknowledge @larsman
      DOC Update what's new

Bastiaan van den Berg (1):
      BUG allow outlier_label=0 in RadiusNeighborClassifier

Ben Root (7):
      This should make the hungarian algorithm accept rectangular cost matrices. Also enabled the tests.
      An additional check needed in case where there are fewer columns than rows.
      Added support for hungarian assignment problems where one dimension of the cost function is zero-length.
      Created an alternative hungarian solver for rectangular matrices that does not involve matrix padding.
      hungarian() now returns a 2-D array of indices instead of a 1-D array. Also modified the find_permutations test to accomodate.
      Some minor changes to docs, and small simplification in code.
      Updating namespace usage from scikits.learn to sklearn

Benjamin Peterson (1):
      ENH import six package for Py2/Py3 compat in a single codebase

Daniel Velkov (1):
      Fix wrong argument name in RFECV docstring

Denis Engemann (27):
      FIX transform tests
      FIX: remove inplace mod
      COSMITS
      FIX: inverse transform + add mean_
      COSMITS
      FIX: syntax typo
      FIX: tutorial
      COSMITS + DOC
      COSMITS
      ENH: improve tutorial to be more clean.
      ENH + FIX: remove inverse-t kwarg + fix mean_
      FIX: address @agramfort 's comments
      FIX: address remaining issues
      ENH: speed up logcosh
      ENH: improve ICA memory profile by 40%
      ENH: add failing test exposing bug in RandomizedPCA
      FIX: only center if copy == True
      ENH: get it right.
      FIX: inverse_transform; tests
      DOC better doc message
      API: get rid of **params in PCA estimators.
      DOC: more doc string fixes in pca.py
      DOC: more fixes in pca.py doc strings
      STY: get rid of unnecessary identifiers
      FIX: X.copy() test now works
      STY: removing unnecessay import
      COSMITS

Denton Cockburn (3):
      DOC fix some docstring/parameter list mismatches
      renamed weight to sample_weight in sklearn/isotonic.py
      DOC missing stuff in randomized_l1 module

Diego Molla (2):
      Minor bug fix in metrics.adjusted_rand_score
      Added tests

Doug Coleman (15):
      FIX: Cast floats to int before slicing in robust_covariance
      BUG: Build random forests the same way regardless of n_jobs and add a test for this. Don't predict in parallel since the cost of copying memory in joblib outweighs the speedups for random forests. Fixes #1685.
      COSMIT: Fix up a loop.
      COSMIT: Better assert.
      DOC: Update new magic numbers in docs since random forests train differently now.
      FIX: sklearn.ensemble.forest: Refactor to remove references to parallelism in predict() functions.
      BUG: Fix performance regression on large datasets in random forest.
      DOC: Emphasize that n_jobs is for fit and predict methods in random forests.
      BUG: Use Py_ssize_t to index into numpy arrays to help Python handle big data.
      MISC: Update _tree.c with cython.
      BUG: Use ``Py_ssize_t`` in a few more places for strides. Add the c file again.
      DOC: Clarify docs on preprocessing.Binarizer.
      FIX: Finish package rename from mst -> sparsetools. Fixes #2189.
      DOC: Fix backwards docs on thresholds for preprocessing.
      FIX: Newer numpy causes scipy to issue a DeprecationWarning. Ignore it. Fixes #2234.

Dougal Sutherland (3):
      StratifiedKFold: remove pointless copy of labels
      stochastic_gradient: fix mistake in _init_t docstring
      stochastic_gradient: describe all losses, fix epsilon description

Eustache Diemert (35):
      added first version of out-of-core example
      revision round #1 (move to examples/applications, 1 file, auto-download dataset)
      pep8 / pep257 compliant formating
      get rif of feature dicts, leverage HashingVectorizer class directly
      plot as both a function of time and n_examples
      using print() function
      improve explanations on out-of-core learning paradigm
      improve explanations on example structure
      fixed use of docstrings + added section in whats_new.rst + added data dir to .gitignore
      more robust data location
      use same, separate held-out data to estimate accuracy after each mini-batch
      added first version of out-of-core example
      revision round #1 (move to examples/applications, 1 file, auto-download dataset)
      pep8 / pep257 compliant formating
      get rif of feature dicts, leverage HashingVectorizer class directly
      plot as both a function of time and n_examples
      using print() function
      improve explanations on out-of-core learning paradigm
      improve explanations on example structure
      fixed use of docstrings + added section in whats_new.rst + added data dir to .gitignore
      more robust data location
      use same, separate held-out data to estimate accuracy after each mini-batch
      fixed conflict in whats_new.rst
      Merge branch 'master' of git://github.com/scikit-learn/scikit-learn into out-of-core-examples
      factorized instance extraction + plots
      added note on test set creation rationale
      cosmit : inline extract_instance
      Merge branch 'master' of git://github.com/scikit-learn/scikit-learn into out-of-core-examples
      more structured iteration using islice + wrappers; renamed chunk for minibatch as the latter seems more common in hte literature
      added sub section on out-of-core scaling in the narrative docs
      Merge branch 'master' of git://github.com/scikit-learn/scikit-learn into out-of-core-examples
      some more language corrections
      more pep257 fixes (not for ReuterStreamReader as it is not really the interesting class here)
      DOC recommend understanding NumPy in the tutorial
      DOC expand feature selection docs with an example

Fabian Pedregosa (11):
      Clarify docstring in lars_path
      Update LIBSVM_CHANGES
      Add SVD-based solver to ridge regression.
      Remove unnecessary code in ridge svd
      BUG: solver was not passed to computational method in Ridge object
      Use Cholesky solver by default, but use SVD as fallback
      Use ValueError for non-existant solvers
      Merge pull request #1914 from fabianp/ridge_svd
      Test for singular matrices in Ridge regression
      Fix broken link to web designer
      Fix broken link to web designer

Fazlul Shahriar (1):
      DOC fix docstring typos in cluster/mean_shift_

Federico Vaggi (5):
      Added test_regressor_pickle to tests.
      Added test_classifiers_pickle to tests.
      Finished adding pickle tests.
      Removed the use of StringIO, using pickle.dumps instead.
      cosmetic: Changed all instances of nonlinear to non-linear

Felix Brockherde (1):
      FIX scores calculation in ovo multiclass

Félix-Antoine Fortin (1):
      DOC/FIX affinity_propagation damping default value.

Gael Varoquaux (93):
      DOC: typo in warning
      BUG: reassignment_ratio == 0 in MiniBatchKmeans
      BUG: sparse center reassignment MiniBatchKMeans
      BUG: sparse vs non sparse centers
      BUG: fix test to use sparse array
      DOC: reference for discretise option
      COSMIT :: in rst is easier for syntax highlighters
      DOC: minor formatting in model_evaluation.rst
      DOC: minor rst issues
      DOC: misc rst formatting
      COSMIT: prettify code and figure in example
      COSMIT
      Merge branch 'treeweights'
      Merge pull request #1656 from rlmv/idf_diag
      BUG: update joblib to 0.7.0d
      TST: add a test for empty reassignment in MBKmeans
      BUG: highly-degenerate roc curves
      BUG: fix change of behavior in last commit
      DOC: add example and ref to lars_path in lasso_path
      BUG: ElasticNectCV choosing improper l1_ratio
      ENH: minor changes for numpy versions
      DOC: remove typo
      DOC: libatlas3-base in requirement
      ENH: Avoid computations in ElasticNetCV
      ENH: improve memory usage in ElasticNetCV
      DOC: docstring of private functions
      BUG: fix sparse support in ElasticNetCV
      COSMIT: address @agramfort's comments
      DOC add 2012 GSOC students
      COSMIT: labels in plot_lasso_coordinate_descent_path
      COSMIT: txt -> rst
      DOC: cosmit - fix latex typo
      ENH: avoid MemoryError on manhattan_distances
      BUG: old versions of numpy
      BUG: old versions of numpy
      MISC: details about the donations
      BUG: type conversion in spectral_embedding
      MISC: remove unused imports
      BUG: restore Python 2.6
      COSMIT: two empty lines between functions
      Merge branch 'pr_1732'
      BUG: fix sparsetools tests in old scipy
      PEP8
      Cosmit
      Merge branch 'pr_2002'
      BUG: fix unsafe casting
      DOC: improve RBM example
      MISC: remove unecessary dtype
      ENH: better error message on scoring
      DOC: reorganize model_evaluation
      MISC: address comments and test failure
      DOC: address remarks by @NelleV
      DOC: Address @larsman's comments
      DOC: @amueller's comments
      ENH: Add the hungarian algorithm
      TEST: Increase testing of hungarian
      MISC: cosmit in hungarian
      ENH: Speed up in hungarian
      ENH: More speedups in hungarian
      ENH: More speedups in hungarian
      ENH: Still more speed ups in Hungarian
      ENH: More speedups on Hungarian
      API: scikits.learn -> sklearn
      BUG: fix some numpy 1.3 compat issue
      BUG: numpy 1.6 compat
      :
      BUG: fix kde tests
      MAINT: update copy_joblib script
      ENH: update joblib to 0.7.1
      MAINT: misc change to copy_joblib
      ENH: make bdist_rpm work
      COMPAT: empty_like does not have a dtype in np 1.3
      COMPAT: fix arpack and pls on old scipy/numpy
      COMPAT: string formatting syntax in Py 2.6
      COMPAT: median and nans in old numpys
      COMPAT: no assert_warns in np 1.3
      BUG: fix Py 3
      DOC: invert priorities bootstrap <-> nature.css
      DOC: sidebar lighter
      ENH: add a new DataConversionWarning
      MISC: fix plot_multilabel example
      BUG: implement concrete __init__ for SGDRegressor
      BUG: tests were raising the DataConversionWarning
      Merge branch 'pr_2304'
      MAINT: recompile Cython files
      DOC: add whats_new on the news
      TST: adjust test relying on change order
      MISC: deprecate balance_weights (it's internal)
      REL: 0.14a1 Release candidate for 0.14
      MISC: update whats_new
      MISC: fix reference to example
      DOC: DBSCAN misc doc formatting
      DOC: also point installation menu to stable

Gilles Louppe (275):
      ENH: weighted r2 score for regression
      COSMITs
      ENH: Added balance_weights
      ENH: added some tests
      FIX: test_oob_score_regression
      FIX: compute weighted oob scores
      FIX: NaN problem + Added some tests
      TEST: added some more tests
      EXAMPLE: simplify n_estimators and n_samples
      TEST: importances
      TEST: multi-output problems
      ENH: WeightedClassifier/Regressor mixins
      DOC
      FIX: drop support for multi-output
      TEST: errors
      ENH: staged_score
      EXAMPLE: reduce the number of samples
      EXAMPLE: merge plot_adaboost_iris into plot_forest_iris
      EXAMPLE: drop plot_adaboost_quantiles
      FIX: move balance_weights into preprocessing
      PEP8 + PyFlakes
      FIX: broken test
      FIX: one more bug
      FIX: remove prints
      DOC: edited some docstrings
      DOC: added references into classes.rst
      ENH: rename boost method to _boost
      DOC: cosmits + narrative documentation (begin)
      DOC: proper citations
      DOC
      TEST: make test_importances more stable
      DOC: narrative documentation
      DOC: What's new
      TEST: base_estimator
      DOC: classes_ and n_classes_
      DOC: put docstrings into subclasses to make them appear in the documentation
      DOC + Better default parameter values
      DOC: cosmits
      DOC: typo
      PEP8 and DOC
      ENH: use shuffle
      Roll back some changes
      Roll back some changes (2)
      Merge branch 'master' of github.com:scikit-learn/scikit-learn into adaboost
      FIX: broken test
      FIX: @amueller comments
      Cosmits, code structure and tests
      EXAMPLE: better plot_adaboost_regression
      Revert changes on plot_adaboost_error.py
      ENH: set default parameter values
      Cleanup
      EXAMPLE: give plot_adaboost_classification some love
      DOC: narrative documentation
      Merge branch 'master' of github.com:scikit-learn/scikit-learn into adaboost
      Merge branch 'master' of github.com:scikit-learn/scikit-learn into adaboost
      FIX: some nitpicks
      ENH: remove boost_method parameter and use a string as switch
      ENH: weights_ -> estimator_weights_
      FIX: pprett comments
      DOC: Added a References section in _samme_proba
      COSMIT: flake8
      ENH: weight -> estimator_weight
      ENH: weight -> estimator_weight (2)
      ENH: weight -> estimator_weight (3)
      EXAMPLE: better x-axis label
      EXAMPLE (2)
      FIX: make_hastie_10_2 reference docstring
      DOC: add a short dataset description in hastie example
      DOC: narrative documentation
      FIX: doctest
      EXAMPLE: add AdaBoost to plot_classifier_comparison
      FIX: some of Gael comments
      What's new: Adaboost
      Remove compute_importances parameter
      What's new
      ENH: Remove compute_importances in AdaBoost
      ENH: Update feature_importances in GBRT
      ENH: remove "mse" method and simplify
      COSMIT
      DOC: feature importances
      Merge pull request #1657 from glouppe/feature-importances
      DOC: add balance_weights to reference
      EXAMPLE: compute_importances=True is no longer required (1)
      EXAMPLE: compute_importances=True is no longer required (2)
      DOC: narrative documentation on feature importances
      ENH: precompute X_argsorted when possible
      DOC: X_argsorted
      Flake8
      ENH: use isinstance instead
      Merge pull request #1668 from glouppe/adaboost-tree
      Merge pull request #1700 from erg/rf
      FIX: use DOUBLE_t type
      Merge pull request #1705 from glouppe/tree-fix
      ENH: support float value for max_features
      DOC: if float, then max_features is a percentage
      ENH: Defer parameter checking of trees
      DOC: GBRT max_features
      TEST: added test
      ENH: use numbers
      FIX: numpy integers
      PEP8
      Merge pull request #1712 from glouppe/tree-maxfeatures
      What's new: float values support for max_features
      What's new: fix indentation
      Merge pull request #1816 from ndawe/master
      Merge pull request #1823 from erg/issue-1466
      Merge pull request #1852 from slattarini/typofixes
      ENH: moved export_graphviz to sklearn/tree/export.py
      ENH: add max_depth to export_graphviz
      ENH: output criterion name instead of "error" in export_graphviz
      Merge pull request #1998 from kgeis/fix-setup-instruction
      Merge pull request #2031 from jnothman/tree_comments
      WIP: new Cython interface for decision trees
      WIP: comments on the Cython interface
      WIP: Criterion interface and base class
      WIP: ClassificationCriterion (reset, update)
      WIP: Gini criterion
      WIP: entropy criterion
      WIP: remove n_left and n_right attributes
      WIP: MSE criterion
      WIP: tree class
      WIP: tree algorithm
      WIP: add_node
      WIP: node_value
      WIP: node_value
      WIP: predict + apply
      WIP: Random Splitter
      WIP: splitter
      WIP: Best Splitter
      WIP: sort features
      WIP: first pass on tree.py
      WIP: some debug
      WIP: some more debug
      WIP: debug in progress...
      WIP: debug (tests still don't pass...)
      WIP: one more bug fixed
      WIP: cleanup
      WIP: one more test fixed
      WIP: more bugs fixed :)
      WIP: 19 tests passed
      WIP: test_tree.py now passes \o/
      Cleanup
      WIP: feature importances
      WIP: discard samples with weight = 0
      WIP: fix export functions
      Cleanup
      WIP: first pass on ensembles
      WIP: use heapsort
      WIP: small optimization to heapsort
      WIP: remove asserts
      WIP: use C-based random number generator
      WIP: set n_classes as ndarray
      FIX: fix test_random_hasher
      WIP: fix adaboost
      WIP: small optim to regression criterion
      WIP: optimize tree construction procedure
      WIP: optimization of the tree construction procedure
      cleanup
      recompile _tree.pyx
      FIX: export_graphviz test
      FIX: set random_state in adaboost
      FIX: doctests
      FIX: doctests in partial_dependence
      FIX: feature_selection doctest
      FIX: feature_selection doctest (bis)
      WIP: allow Splitter objects to be passed in constructors
      FIX
      Some PEP8 / Flake8
      Small optimization to RandomSplitter
      FIX: fix RandomSplitter
      Cosmit
      FIX: free old structures
      WIP: Added BreimanSplitter
      WIP: small optimizations
      WIP: fix BreimanSplitter
      Cleanup
      WIP: optimize swaps
      Regenerate _tree.c
      WIP: some optimizations to criteria
      WIP: add -O3 to setup.py
      WIP: normalize option for compute_feature_importances
      WIP: Added deprecations in tree.py
      WIP: updated documentation in tree.py
      WIP: added deprecations in forest.py
      WIP: updated documentation
      WIP: unroll loops
      WIP: setup.py
      WIP: make sort a function, not a method
      WIP: Cleaner Splitter interface
      WIP: even cleaner splitter interface
      WIP: some optimization in criteria
      WIP: remove some left-out comments
      WIP: declare weighted_n_node_samples
      WIP: better swaps
      WIP: remove BreimanSplitter
      WIP: small optimization to predict
      WIP: catch ValueError only
      WIP: added some documentation details in _tree.pxd
      WIP: PEP8 a few things
      Benchmark: use default values in forests
      WIP: remove irrelevant and unstable doctests
      WIP: address @ogrisel comments
      WIP: address @ogrisel comments (2)
      WIP: remove partition_features
      WIP: style in _tree.pyx
      WIP: make resize a private method, improve docstring
      WIP: use re-entrant rand_r
      FIX: doctest in partial_dependence
      WIP: break or shorten some long lines
      FIX: doctest in feature_selection
      WIP: break one-liner if statements
      WIP: revert use of rand_r
      FIX: broken tests based on rng
      DOC: update header in rand_r.c
      TEST: skip test in feature_selection (too unstable)
      FIX: one more doctest
      WIP: Faster predictions if n_outputs==1
      WIP: Break comments on new line
      WIP: make criteria nogil ready
      WIP: enforce contiguous arrays to optimize construction
      WIP: avoid data conversion in AdaBoost
      WIP: use np.ascontiguousarray instead of array2d
      TEST: add test_memory_layout
      FIX: broken test
      WIP: Make trees and forests support string labels
      WIP: refactor some code in forest.fit
      TEST: skip doctest in feature_selection (unstable)
      WIP: better check inputs
      WIP: check inputs for gbrt
      Merge pull request #2131 from glouppe/trees-v2
      What's new: new implementation for trees
      FIX: remove debug message
      FIX: remove -funroll-all-loops
      FIX: ur strings are not supported in Python 3.3
      DOC: some documentation for the Tree Cython structure
      Merge pull request #2216 from glouppe/tree-doc
      Benchmark: use specified dtype
      TEST: cosmit on err_msg
      Raise an exception if rows are full of missing values
      FIX: doctest
      Better error message
      FIX: use range instead of xrange
      FIX: imputation example
      Merge pull request #2241 from arjoly/grid-cv-multioutput
      Merge pull request #2262 from NicolasTr/fix_statistics
      FIX: remove blank lines
      Use epsilon=1e-7
      FIX: partial dependence test
      TEST: skip test_oob_multilcass_iris for now
      Merge pull request #2277 from glouppe/tree-fix-32bits
      COSMIT: typo in examples/imputation.py
      Mr. Proper, act 1
      Banner improvements
      Banner style
      Boxes on front page
      Load bootstrap first
      FIX: footer character encoding
      CSS tweaks
      CSS tweaks (2)
      Lower part of the index
      CSS tweaks
      More css tweaks
      Better alignment in the sidebar
      CSS tweaks
      More css kungfu
      CSS stuff
      Remove testimonials for now
      CSS tweaks
      Donate button + citing
      Enhance contrasts
      Contributin
      Remove toc on the API page (it is already in the sidebar)
      FIX: sidebar.js
      Move Google javascript near </body>
      FIX: remove dupplicate entry in What's new

Harikrishnan S (1):
      DOC/FIX twenty_newsgroups.rst should use TfidfVectorizer

Hrishikesh Huilgolkar (7):
      chi2 and additive_chi2 raise error if input are sparse matrices
      Added same for additive_chi2_kernel
      Fixed pep8 issues
      pairwise_distance_functions renamed to PAIRWISE_DISTANCE_FUNCTIONS
      Made more changes renamed pairwise_kernel_functions, kernel_params to allcaps
      Added test for fit_transform(X)==fit(X).transform(X)
      Fixed pep8 issues

Ian Ozsvald (3):
      clearer decision surface plots and classifier final predictions for the ensembles
      improved formatting
      updated docs to fix formatting errors

Imran Haque (2):
      ENH Release GIL when entering LibSVM/Liblinear code
      Release GIL around sparse liblinear training

Jack Hale (1):
      WMinkowskiDistance corrections to error messages and docstring

Jake VanderPlas (75):
      BUG update graph_laplacian to upstream SciPy version
      Ball Tree, KD Tree, and tests
      Fix tests for scipy <= 0.9
      speed up KD tree construction by ~25%
      add author & license information to pyx files
      add median of 3 pivoting to quicksort
      add pydist code
      fix binary tree sort bug
      add pydist: user-defined metric
      add haversine distance
      add exception passing to C functions
      rename dist conversion funcs
      Implement correct d-dimensional kernel norms
      add metric mappings to dist_metrics
      binary tree: make valid_metrics a class variable
      dist_metrics: allow callable metric
      add chebyshev distance to kd tree
      add functionality to NearestNeighbors estimators
      Roger-Stanimoto -> Rogers-Tanimoto
      calculate kernel norm only once
      compute kernel norm only once
      TST: compare gaussian KDE against scipy version
      Change dual splits to single splits in query_dual
      Merge pull request #7 from jhale/new_ball_tree
      add notes on implementation details to binary_tree.pxi
      remove scipy cKDTree support from neighbors
      add neighbors module changes to whats_new
      Merge pull request #2104 from kastnerkyle/master
      BUG: fix precision issues in kernel_density; remove buggy dual-tree KDE versions
      add KDE Estimator class
      add kwargs to PyFuncDistance
      DOC: document the new neighbors functions & KDE
      undo change to clustering example
      fix conflicts with master
      import KernelDensity from neighbors module
      adjust math formatting in neighbors docs
      fix NearestNeighbors to pass common tests
      add KernelDensity to class list
      set random seed in KDE example
      skip KDE test to prevent failure due to older SciPy versions
      fix typo: SkipTe -> SkipTest
      fix doctest in neighbors
      BUG: return proper algorithm in KDE
      add species KDE example
      PEP8: neighbors module
      DOC: rearrange KDE examples
      TST: increase test coverage in neighbors module
      DOC: pep8 & formatting in neighbors docs
      DOC: make doc tests pass
      add 1D KDE example
      DOC: small fixes to neighbors doc
      DOC: move KDE discussion to separate page
      add some notes and doc strings to neighbors cython code
      add more documentation to ball tree and kd tree
      DOC: tweak kde examples and move density docs
      BUG: fix tophat sampling in KDE
      Xplot -> X_plot
      bt->tree; dm->dist_metric
      Additional implementation notes in binary tree
      BUG: use correct algorithm for callable metric
      TST: set random state in callable_metric test
      BUG: add new preprocessing module to setup.py
      Merge pull request #2264 from jakevdp/setup_fix
      neighbors numpy1.3 compat: fix typedefs, regen with cython 0.19
      numpy 1.3 compat: use explicit type definitions
      numpy 1.3 compat: make neighbors/dist_metrics compatible
      COMPAT: make NeighborsHeap compatible with numpy 1.3
      COMPAT: make NodeHeap compatible with numpy 1.3
      COMPAT: make BinaryTree class compatible with numpy 1.3
      COMPAT: make BallTree & KDTree compatible with numpy 1.3
      COMPAT: last few BallTree/KDTree numpy 1.3 issues
      BUG: type->dtype in a cross-platform way
      compute offset in a cross-platform way
      BUG: don't subtract offset in binary_tree
      add explicit types to neighbors cython code

JakeMick (1):
      TST added test of fit and transform for kernels for nystroem

James McDermott (1):
      DOC rename lambda to alpha in plot_lasso_coordinate_descent_path. (Re)-Closes #903.

Jaques Grobler (103):
      remove the equaldistance code warning, replace with doc warnings
      typo fix
      remove warning
      warning removal
      update warning box
      deprecation warnings, indent fix
      andys suggestions and test
      add warning for no internet
      Merge pull request #1644 from jaquesgrobler/doc_url_error
      TYPO fix
      example title change
      gallery effects,icon change,cleanups
      typo fix and heading changes
      fix indentation error-cause lots of build warnings
      4 thumbs per row/hover effect/some cleanup
      fix for iris dataset
      line_count sort added, some changes reverted
      move comment out of list
      remove comment, undo change
      Merge pull request #1803 from kmike/hmm
      rename example title
      Switch off survey banner
      newline at end of file
      Merge pull request #1581 from jaquesgrobler/example_gallery_cleanup
      temp disable line-count-sort for gallery while fixing bug
      sort-by-line-count bug fixed
      Merge branch 'master' of github.com:scikit-learn/scikit-learn
      fix numbering for tutorials page
      Add bit more instruction on writing docs
      big O/tilde add in
      removed old complexity info
      image and html file added
      link fixes
      add further links
      last links fixed
      jquerys added
      intigrated to tutorial index
      update tutorial page
      make links relative
      rename image/html
      add instructions for editing Readme, and script needed for that
      remove svg2html script,toctree section added,doc page for ml_map created
      sidebar added
      layout fixes and top paragraph
      TYPO fix
      update what`s new
      deleted unnecessary thumbnail
      DOC improve description of cross validation
      resized image
      disable sidebar using cookies to remember last position
      COSMIT pep8
      Merge pull request #1884 from jaquesgrobler/ml_map
      DOC added link to scipy lecture notes to tuts
      Merge pull request #1924 from jaquesgrobler/FIX_sidebar_on_index_page
      Merge pull request #1911 from Jim-Holmstroem/generalize_label_type_for_confusion_matrix
      Merge pull request #1944 from jnothman/selectpercentile_limit_bug
      fixed typo
      maintenance scripts added for machine learning maps - needed for modifying the map in future
      DOC Fix references to missing examples
      fix incorrect reference
      Merge pull request #1986 from jaquesgrobler/DOC_reference_fixes
      add optional banner to index page to advertise code sprints
      link updated
      Merge pull request #1996 from jaquesgrobler/DOC_sprint_sponser_banner
      hover removed from nature, jquery more recent version, containerexpansion on mouseover add
      image resizing added
      Zoom bug fixed
      added docstring space to popup block
      docstrings embedded into example hovers
      Final visual effects added to hovering
      Nelle`s review fixes addressed
      Cross browser shadows covered
      remove forgotten print
      shorten displayed dosctring to 95 chars
      fix white space inconsistency between header and docstring
      example docstring fixes
      logistic regresion example fix
      Merge pull request #2056 from jnothman/leavepout_clarify
      firefox bug fixed
      classifiers comparison fix
      DOC spellfixes
      Donate buttons added `About us` and front page
      donations paragraphs added
      Merge branch 'master' of github.com:scikit-learn/scikit-learn
      misalignment fix
      example fixes to clean first docstring paragraph of rst code
      fix merge conflict
      border added for IE
      make new classes for lasso_path/enet_path and deprecate old
      rel_canonical prelim
      Merge branch 'master' into ENH_docstrings_in_gallery
      syntax fix
      cleaned up-ready
      Merge pull request #2017 from jaquesgrobler/ENH_docstrings_in_gallery
      Small docstring changes for plot_ward_structured_vs_unstructered example, as mentioned in PR #2017
      nitpick fixes, pep8 and fix math equations
      removed old_version block test
      Merge pull request #2205 from jaquesgrobler/ENH_rel_canonical
      sidebar fix - sidebar.js was called before jquery. works fine under new version jquery too
      sidebar/toctree harmonie, must still fix toggle
      jquery reverted to 1.7.2 version. sidebar/toc-collapse works
      DOC: few small doc fixes to layout bugs on new website
      comments added to the changes

Jim Holmström (10):
      Added random_state=0 for AdaBoostRegressor
      Replaced 'for i' with 'for _' at place where i is not used.
      Extended test_confusion_matrix_binary to incorporate non-integer labels
      Extended test_confusion_matrix_multiclass to incorporate non-integer labels
      BUG: Fix for non-integer datatypes in confusion_matrix
      ENH: faster preallocation and integer type for the accumulators
      STY: one-lined lines that where less than 79
      MAINT: let the result type be infered by coo_matrix, possible since np.ones already integer typed
      MAINT: refactored metrics.auc to use np.trapz
      ENH: Added input checks in confusion_matrix

Jochen Wersdörfer (2):
      ENH CountVectorizer using arrays instead of lists
      ENH added multiclass_log_loss metric

Joel Nothman (79):
      Fix comment: returns fbeta_score, not f1_score
      ENH allow SelectKBest to select all features in a parameter search
      DOC Allowing a list of param_grids means GridSearchCV is more than grids
      DOC clarify relationship between pos_label and average parameters for
      ENH/FIX make best_estimator_'s predict functions available in parameter search
      FIX make *SearchCV picklable
      REFACTOR combine train_wrap and csr_train_wrap
      ENH call asarray on returned scores and pvalues
      TST ensure SelectKBest and SelectPercentile scores are best
      FIX ensure SelectPercentile only removes tied features in case of ties
      ENH _BaseFilter.inverse_transform should respect dtype
      DOC Fix comment for _BaseFilter.inverse_transform
      ENH sparse _BaseFilter.inverse_transform
      FIXTST fix errors introduced to feature selection tests
      DOC comment feature selection sparse inverse_transform
      Merge pull request #1935 from jnothman/base_filter_inv_transform
      ENH Feature selection should use CSC matrices
      COSMIT Remove redundant code in CountVectorizer
      TST test CountVectorizer.stop_words_ value
      ENH Use csr_matrix.sum_duplicates instead of tocoo
      DOC small typographical fixes in grid_search documentation
      COSMIT refactor roc_curve and precision_recall_curve
      FIX bug where hinge_loss(..., neg_label=1) produced incorrect results
      Merge pull request #1880 from NicolasTr/patch_extractor_float_max_patches
      DOC Fix estimator unsupervised fit method signature
      DOC clarification of parameter search
      DOC fix typos
      COSMIT shorten long line for pep8
      ENH Create FeatureSelectionMixin for shared [inverse_]transform code
      DOC rewrite descriptions of P/R/F averages and define support
      DOC/COSMIT fix typos in What's New
      DOC add some contributions to What's New
      TST Use assert_almost_equal in test_symmetry
      COSMIT prefer partial over lambda in test_metrics
      TSTFIX use name, not metric, in test_metrics error messages
      DOC correct note on handling 0-denominator in P/R/F
      Merge pull request #2005 from kmike/test_pipeline_methods_preprocessing_svm
      ENH faster unique_labels for big sequences of sequences
      DOC explain labels parameter to confusion_matrix
      DOC Detail on parent-child relationship in tree
      FIX/COSMIT helper to identify target types
      FIX cannot use set notation for Py2.6
      FIX need explicit dtype for array of sequences in numpy 1.3
      COSMIT remove redundant target size check
      FIX numpy 1.3 has no float16; use float32
      FIX/TST np.squeeze in numpy1.3 fails with array of sequences
      FIX numpy 1.3 throws error with array of arrays
      FIX use Python 2.6-compatible str.format
      COSMIT refactor cross-validation strategies
      Include LeavePLabelOut in refactoring
      A further refactor
      COSMIT Base class for KFold/StratifiedKFold validation
      COSMIT make BaseKFold abstract
      COSMIT pep8 in cross_val_score
      COSMIT Base class for [Stratified]ShuffleSplit
      DOC clarify LeavePOut's combinatoric explosion
      DOC similar note in narrative docs
      DOC More explicit note
      DOC fix docstring headings
      COSMIT make helpers private with underscore
      COSMIT make BaseKFold private with underscore
      TST additional tests for preprocessing.Binarizer
      COSMIT add underscore prefixes where forgotten in cross_validation
      COSMIT much simpler agglomeration inverse_transform
      TST stronger test for agglomeration transforms
      DOC minor fixes to Ward docstrings
      DOC fix docstrings for AgglomerationTransform
      DOC detail Ward.children_ and fix n_components_ type
      DOC comment on Ward algorithm
      DOC clean pooling_func arg type
      DOC copy comment describing hierarchical clustering children
      Merge pull request #2054 from ogrisel/invalid-n-folds
      FIX avoid spectral_embedding naming conflict
      Merge pull request #2085 from agramfort/fix_y_score_fa
      Merge pull request #2090 from kanielc/fix_weight
      COSMIT move deprecated parameter to end
      COSMIT refactor document frequency implementations
      ENH print number of fits in BaseSearchCV._fit
      DOC fix comment on svm probability param

Johannes Schönberger (3):
      Remove invalid todo comment
      Add missing doc string printing for examples
      DOC : fixes in covariance module

John Benediktsson (1):
      COSMIT: fix excessive indentation.

John Zwinck (1):
      FIX use float64 in metrics.r2_score() to prevent overflow

Joshua Vredevoogd (1):
      DBSCAN BallTree implementation

Justin Pati (1):
      changed warnings in grid_search.py related to loss_func and score_func being passed

Justin Vincent (19):
      PY3 xrange, np.divide, string.uppsercase, None comparison
      TST + PY3 various fixes
      Got all the doc-tests working
      Merge in master
      More python3 fixes (and just plain bugs)
      use ELLIPSIS in doctest to deal with numpy changes.
      Forcing the deprecation warnings to happen while in get_params.
      Force warning to be heeded in deprecated args check. Possibly fixed a test bug (but maybe I just got it wrong)
      Make a test not dictionary order dependent.
      Fix up last doc tests.
      Make the fixes 2.6 compatible
      ELLIPSIS around a unicode issue.
      Fix y vector. We wanted round off division so that y == [0 0 1 1 2 2 ...], not [0 .5 1 1.5...]
      A little more of those unicode helpers
      Another ELLIPSIS
      Pop off the recently added filter after testing for deprecation warnings.
      merge in origin
      Comment change
      Fix two remaining python3 bugs.

Kemal Eren (99):
      ridge regression uses compute_class_weight()
      Re-add deprecated class_weight parameter.
      removed class_weight parameter from RidgeClassifier.fit()
      check_pairwise_arrays() preserves dtype==numpy.float32
      implement spectral biclustering and spectral co-clustering
      wrote tests
      wrote methods for generating bicluster data
      added option to return piecewise vectors
      cast data in fit()
      made internal functions private
      use random state in test
      removed pickle test
      shorten first lines of test docstrings
      use random state in preprocess tests
      duck typing, minor corrections: spacing and typos
      fixed exceptions and their messages
      updated svd()
      better array validation
      use random state in data generator
      tests reuse data generators
      user may select svd method
      Added to docstring
      split spectral biclustering into two classes
      removed unused code
      test bad arguments
      now supports sparse data
      check n_clusters parameter more thoroughly
      made base class an abstract class
      checkerboard panels may have arbitary values.
      fixed exception type
      removed empty mixin
      started biclustering documentation and examples
      shorter array slicing
      made some methods into private methods
      cleaner use of check_arrays()
      named arguments
      use safe_sparse_dot()
      use np.random.RandomState directly
      do not do any checks during __init__()
      do not use mutable default arguments
      added new tests for sample data generators
      fixed bug in make_checkerboard(), so tests pass again
      use assert_all_finite
      skip permutation test for now
      fixed some errors reported by pyflakes
      raise exception instead of converting sparse arrays to dense
      expanded biclustering documentation
      corrected k_means in docstring
      rearranged imports from general to specific
      moved and renamed _make_nonnegative() and _safe_min()
      added option to use mini-batch k-means
      use dia_matrix
      renamed 'preprocess' to 'normalize'
      use sklearn.utils.extmath.norm
      base class __init__ is no longer abstract
      added more information to error messages
      also use norm in _project_and_cluster()
      make test more sparse
      made 'bicluster' a submodule of 'cluster'
      removed svd_kwargs argument
      added n_svd_vecs parameter
      tests use ParameterGrid to avoid deep nesting
      replaced kmeans_kwargs with some useful k-means parameters
      updated documentation
      keep biclustering algorithms in submodule
      renamed examples; added to example docstrings
      re-added bicluster mixin, this time with some functionality
      wrote newsgroup biclustering example
      fixed a few things in examples, documentation, and docstrings
      wrote bicluster scoring using jaccard index and hungarian matching
      removed some parameters to speed up test
      added default arguments to base class's__init__ to make test pass
      test_make_checkerboard was wrong after api change
      added documentation for bicluster evaluation
      moved shuffle functionality to utility function
      added consensus score to bicluster examples
      renamed example to get output to work
      made bicluster utilities for dealing with indicator vectors
      index in one go. added sparse test.
      documentation and docstring fixes
      merged newsgroup example with Vlad's
      moved bicluster examples to their own category
      reduced noise in spectral coclustering example
      updated newsgroups example
      added n_discard parameter to _svd()
      check value of n_components and n_best
      a fix for nan values in singular vectors.
      wrote tests to ensure svd works on perfect checkerboard
      redundant phrase in docstring
      put biclustering section after clustering section in reference
      misc. fixes
      changes to newsgroups example:
      fixed some docstrings: backticks and missing parameters
      updated setup.py
      added myself to authors; added biclustering to whats new
      examples use matplotlib.pyplot instead of pylab
      consistency changes:
      removed plot_ from newsgroups example file
      import biclustering methods in sklearn.cluster and sklearn.metrics.cluster

Ken Geis (4):
      Changed the setup instructions in the README to properly install the package in the user home.
      FIX mbkmeans benchmark bug (k instead of n_clusters)
      FIX off-by-one error in neighbors benchmark
      ENH lots of benchmarks fixes

Kevin Hughes (1):
      ENH actually use scikit-learn's PCA class in plot_pca_3d.py

Kyle Kastner (6):
      Removed pl.axis('tight') and set the plot limits with pl.xlim(), pl.ylim(). pl.axis('tight') appears to be adding whitespace around the colormesh
      Added decision_function support to OneVsRestClassifier and a test, test_ovr_single_label_decision_function, in test_multiclass.py
      Updated fixes for #2012.
      Strengthened tests for OneVsRestClassifier decision_function
      Cleaned up tests, and removed unused multilabel parameter in decision_function_ovr
      Inlined extraneous function call from decision_function and added a check that the base estimator has a decision_function attribute

Lars Buitinck (244):
      COSMIT rm deprecated svm.sparse module
      COSMIT rm deprecated attrs from [LQ]DA
      BUG last references to svm.sparse
      COSMIT rm deprecated stuff
      BUG fix failing doctest
      BUG one more failing doctest
      BUG move label_ from BaseLibSVM to BaseSVC
      COSMIT decouple regression and classification in SVMs
      BUG in RadiusNeighborClassifier outlier handling
      Merge pull request #1576 from mrorii/fix_kneighbors
      ENH rewrite radius-NN classifier's outlier handling
      COSMIT translate lgamma replacement to C and clean it up
      COSMIT add lgamma to gitattributes
      DOC update SMART notation in TfidfTransformer docs
      P3K: use print as a function in the examples
      ENH refactor univariate feature selection
      P3K use six.string_types and six.PY3
      P3K one more iteritems
      COSMIT rm Python 2.5 and Jython compat from six
      BUG fix import problem in preprocessing
      P3K StringIO vs BytesIO
      DOC fix failing doctest due to unicode_literals
      DOC whitespace in doctest
      BUG revert P3K changes that broke mldata tests
      rm gender classification example
      P3K death to the print statement
      P3K fix broken doctest and add forgotten print_function import
      DOC no more need for compute_importances in trees
      DOC copyedit FeatureHasher narrative
      ENH move covtype loading to sklearn.datasets
      TST covertype loader
      DOC copyedit FeatureHasher narrative further
      P3K range vs. xrange
      Merge pull request #1524 from amueller/break_ovo_ties
      DOC pretty math in kernel docstrings
      BUG MinMaxScaler missing from preprocessing.__all__
      BUG in KernelPCA: wrong default value for gamma
      Merge pull request #1688 from hrishikeshio/fit_transform
      ENH speed up RBFSampler by ~10%
      BUG oops, removed validation by accident
      BUG fix broken grid search example
      COSMIT update mailmap
      ENH sparsify method for L1-reg linear models
      DOC developer guidelines for unit tests and classes_
      DOC dev guide: random_state_ + @amueller's remarks
      DOC r2_score may return negative values
      Merge branch 'sparse-coef'
      COSMIT callable instead of hasattr __call__
      DOC rm failing doctest on graph_laplacian
      DOC fix text vectorizer docs and add NLTK example
      DOC fix broken doctests for feature_extraction.text
      BUG restore empty vocabulary exc in CountVectorizer
      ENH prevent copying of indices in CountVectorizer
      DOC credit @ephes
      Merge pull request #1713 from larsmans/vectorizer-memory-use
      COSMIT use callable instead of hasattr
      Merge pull request #1727 from amueller/min_max_scaler_fix
      BUG broke the what's new while rebasing
      ENH set min_df in fe.text back to 1
      TST compute_class_weight in utils
      FIX + TST + DOC compute_class_weight
      ENH use bincount in compute_class_weight
      BUG use fixes.unique
      BUG in SVM tests
      BUG fix compute_class_weights issue in SGD
      Merge pull request #1753 from NelleV/FIX
      P3K some more fixes in random places
      DOC OpenBLAS is more dangerous than I thought
      DOC oops, typo
      COSMIT get rid of undocumented attributes on SVMs
      PEP8 and allow non-bool truth values in CD
      BUG + ENH: removal of components in kernel PCA
      Merge pull request #1758 from larsmans/kernelpca-fix
      P3K make feature_extraction.text work
      BUG failing doctest
      DOC IsotonicRegression wasn't in the changelog at all
      P3K all of feature_extraction passes tests on Py2 and 3
      DOC clarify column ordering in SVC scores
      COSMIT DictVectorizer.inverse_transform readability
      DOC CountVectorizer does NOT do stopword filtering by default
      ENH don't recompute distances in MBKMeans
      ENH cut MiniBatchKMeans memory usage in half for large n_clusters
      DOC installation instructions: MacPorts, fix types, stdeb instructions
      Merge pull request #1773 from jnothman/prf_docstring
      BUG StandardScaler would ignore with_std for CSR input
      BUG SGDClassifier and friends did not forget labels_ in re-fit
      DOC clarify C parameter on LogisticRegression
      TST + DOC + COSMIT refactor ParameterGrid and test it
      ENH len on ParameterGrid and ParameterSampler
      BUG deprecation of grid_scores_ in GridSearchCV
      BUG always do cross-validation in GridSearchCV
      DOC fix clone and get_params documentation
      TST grid search/randomized search on non-BaseEstimator
      TST actual sparse input in sparse k-NN tests
      COSMIT prevent a copy in randomized LR
      TST speed up comment tests by ~20%
      TST radius-neighbors regression test not entirely stable
      BUG additive_chi2 missing in KERNEL_PARAMS
      BUG + DOC fix Nystroem for other kernels than RBF
      COSMIT rm repetitive __main__ blocks from tests
      ENH allow additional kernels on KernelPCA
      TST fix broken doctest
      P3K developer docs
      Merge branch 'pr/1790' -- Python 3 support from PyCon sprint
      Merge pull request #1812 from kmike/testing-fixes
      DOC describe SVM probability calibration (and advise against it)
      DOC further comments on SVM probabilities
      ENH multiclass probability estimates for SGDClassifier
      BUG digits grid search was passing cv to the wrong method
      DOC typos in grid search docstrings
      PY3 + TST decouple test_metrics from random module
      Merge pull request #1836 from kmike/master
      DOC distributions produced by hashing trick depend on input
      DOC multiclass: typo and use case
      DOC PR means pull request
      FIX BytesIO and urllib usage in fetch_olivetti_faces
      DOC I didn't mean soft-O by "tilde notation"
      DOC describe API, not internals, for AdaBoost
      DOC replace "arithmetical order" in AdaBoost docs
      TST strengthen AdaBoost tests
      FIX SVR complaining about a single class in the input
      COSMIT do np.unique(y) once in SVC
      DOC rewrite description of k-fold CV
      mailmap entry for @lqdc
      DOC define validation before cross validation
      DOC typos in cross-validation description
      clean up mailmap/deduplicate contributors
      BUG disable memory-blowing SVD for sparse input in RidgeCV
      FIX DictVectorizer behavior on empty X and empty samples
      TST + DOC AdaBoostClassifier.predict_proba fix
      COSMIT refactor AdaBoost code
      ignore PDFs
      ENH speed up sklearn.feature_selection.chi2
      DOC dependency installation with yum (Red Hat, CentOS)
      FIX bug (swapped args) in chi2
      FIX yet another chi2 bug
      ENH add latent semantic analysis/sparse truncated SVD
      ENH use rnd SVD in TruncatedSVD by default for speed
      COSMIT omit unused parameter/return value in svd_flip
      TST strengthen TruncatedSVD tests
      DOC + MAINT deprecate RandomizedPCA scipy.sparse support
      FIX and link LSA clustering example
      DOC explain normalization in LSA KMeans example
      Merge pull request #1716 from larsmans/truncated-svd
      FIX metrics/scoring bug with LeaveOneOut CV
      MAINT remove deprecated gprime handling from FastICA + refactoring
      Merge pull request #2067 from jnothman/test_binarizer
      DOC no more mention of the Bunch in the narrative docs
      FIX don't rely on Bunch behavior with fetch_covtype
      DOC fix some docstring/parameter list mismatches
      DOC fix RandomizedPCA docstring for n_components=None
      ENH allow empty grid in ParameterGrid
      MAINT ignore kernprof.py reports
      DOC ParameterGrid on lists
      Merge pull request #2082 from larsmans/empty-parameter-grid
      DOC fix V-measure docstring
      MAINT dedup Clay Woolam's contribs (>100 commits!)
      FIX/ENH mean shift clustering
      DOC typo
      ENH micro-optimize RFECV
      COSMIT refactor LibSVM wrapper for safety and readability
      DOC fix some broken URLs
      FIX charset -> encoding in load_files
      DOC typo
      Revert "FIX charset -> encoding in load_files"
      FIX verbose output from k-means
      FIX remove params from RandomizedSearchCV
      FIX charset -> encoding in load_files
      FIX search bug introduced in 1327057f4258f41712ecab5c94770aac5ff01982
      FIX inconsistent attributes shapes in naive Bayes
      FIX test failure in naive Bayes
      FIX failing doctest for CountVectorizer
      Merge pull request #2027 from mblondel/select_categorical
      FIX copy in OneHotEncoder and _transform_selected
      ENH optimize KMeans for sparse inputs
      FIX KMeans bug; argsort result apparently not always C-contiguous
      DOC what's new: faster KMeans
      DOC more explicit description of degree param on SVMs
      COSMIT pep8
      ENH order *does* matter for sparse matrices
      FIX get rid of the last few asanyarray calls
      DOC fix erroneous docstring on preprocessing._transform_selected.
      MAINT: dedup @jakevdp and @jnothman in mailmap
      COSMIT simplify printing of number of fits in grid search
      COSMIT fix a docstring in feature_extraction.text
      P3K developer docs
      TST r2_score float32 overflow fix
      Revert "TST r2_score float32 overflow fix"
      PY3 use urllib2 or urllib.request, based on Py2/3
      DOC let OneHotEncoder, DictVectorizer and FeatureHasher refer to each other
      DOC correct class_weight description for LogisticRegression
      FIX memory usage in DictVectorizer.fit
      ENH back-port rand_r from 4.4BSD
      FIX move rand_r to tree module for now
      DOC 20news filtering with smaller set and MultinomialNB
      PY3 fix string literal syntax error
      TST skip Graphviz export docstring in trees
      TST use TruncatedSVD in random forest tests
      COSMIT refactor random forests
      COSMIT refactor forests, part 2
      FIX faulty import in 20news docs
      ENH fit_inverse_transform for FastICA
      DOC document mixing_ attr on FastICA
      COSMIT attribute checking in FastICA
      COSMIT explicit None check in naive Bayes
      ENH simplify the Scorer API
      FIX bug in scorers that take probabilities
      COSMIT RBM test in usual nose style + moved to proper module
      BUG + COSMIT + ENH RBMs
      Merge branch 'pr/1954'
      MAINT _logistic_sigmoid.c is "binary"
      PY3 fix RBM test
      DOC copyedit RBM docstrings
      DOC pep257 + c/e in sklearn.base
      TST fix string labels in metrics tests
      DOC copyedit preprocessing docs
      MAINT ignore profiling results from kernprof.py
      DOC copyedit KernelCenterer docstring
      DOC minimal kernel centering narrative docs
      DOC minor copyedit to FS docs
      Merge pull request #2230 from pprett/neighbors-segfault-fix
      TST catch deprecation warning in feature_extraction.text
      Merge branch 'pr/2246'
      DOC correct/copyedit linear model docstrings
      FIX inline rand_r to fix build on Windows
      DOC add an extremely simple classifier code example to dev docs
      ENH rewrite multiclass_log_loss, rename log_loss, document it
      ENH Scorer object for log loss
      ENH add log_likelihood_score as -log_loss
      PY3 new overfit prevention stuff in 20newsgroups loader
      DOC SGDClassifier has multiclass predict_proba
      DOC minor copyedit to narratives
      FIX don't use old scoring API in randomized search
      FIX use category and stacklevel=2 for {loss,score}_func
      ENH speed up BernoulliNB's predictions
      DOC "creating features" -> "feature extraction" + minor stuff
      Revert "ENH add log_likelihood_score as -log_loss"
      DOC copyedit example docstring
      DOC XHTML fixes (unclosed tags, type="text/javascript")
      ENH speed up logistic_sigmoid (using less code)
      FIX make BaseSGDClassifier an ABC
      Merge pull request #2295 from larsmans/fast-sigmoid
      DOC credit to @ephes and myself for log loss in metrics
      DOC copyedit SGDClassifier docstring

Martin Luessi (6):
      WIP: doc hyperlinks, fixed size thumbnails
      gzip support, whats_new
      use Sphinx searchindex.js
      no_image.png for examples w/o thumbnail
      fix paths for Windows
      links for scipy, cleanup

Mathieu Blondel (53):
      Merge pull request #1604 from darkrho/doc-linear-model-typo
      DOC: make distinction between evaluation and pairwise metrics.
      Merge branch 'master' of github.com:scikit-learn/scikit-learn
      Cosmit: more explicit xlabel.
      Cosmit: more explicit label.
      Update load_svmlight_file docstring.
      FIX: X was converted twice.
      Merge pull request #1804 from AlexanderFabisch/fix_example_path
      Cosmit: remove needless blank lines.
      Cosmit: more idiomatic way of clipping to zero.
      Demystify magic values in NNLS implementation.
      BUG: fix replacement for _neg.
      Fix random state where appropriate.
      Fixx doctest.
      DOC: document attributes fitted by DictVectorizer.
      DOC: put feature extraction before pre-processing.
      COSMIT: better notation in CountVectorizer.
      COSMIT: same changes in transform method.
      COSMIT: more robust condition in inverse_transform.
      Import gzip and bz2 only if necessary.
      Move balance_weights out of preprocessing.
      Add categorical_features option to OneHotEncoder.
      Support both masks and arrays of indices.
      Typo.
      Rename _apply_transform to _transform_selected and make it a function
      Merge branch 'master' of github.com:scikit-learn/scikit-learn into select_categorical
      Address @jnothman's comments.
      Test exception is raison when number of targets and penalties don't
      Simplify ridge solvers (ongoing work).
      Extract sparse_cg and lsqr solvers.
      Extract dense_cholesky solver (linear case).
      Extract dense_cholesky solver (kernel case).
      Clean up.
      Extract SVD-based solver.
      Clean ups.
      Remove copy option.
      Cosmit in docstring.
      What's new.
      Remove if statement.
      Cosmit.
      Fix failures in grid search.
      Do not set sample_weights unless need to.
      Add warning when fall back to other solver.
      Remove unused variable.
      Fix failure in svd-based ridge solver w/ old numpy.
      BUG: replace elif by if in Ridge solver selection.
      Add fit_transform to FastICA.
      Add inverse_transform to FastICA.
      Add docstrings to methods in FastICA.
      Address @dengemann's comments.
      Add test.
      Push failing test.
      Merge pull request #2229 from larsmans/kernel-center-narrative

Matthias Ekman (1):
      ENH: add pre_dispatch option to cross_val_score

Michael Eickenberg (14):
      ridge multi target with individual penalties written. To be tested
      old tests passing
      new multiple target tests added, functionality confined to direct usage of ridge_regression function
      Ridge estimator works with individual penalties
      test for ridge estimator
      ridge doc string
      ValueError for wrong shaped input instead of assertion failure, in order for sklearn/tests/test_common.py, line 238 to pass
      docstring in Ridge estimator
      added individual penalties function for all other solvers. Tests passing for all of them
      always make alpha into an array
      updated tests
      tests passing
      removed elaborate testing in ridge.fit, not necessary anymore
      simplified _solve_svd

Mikhail Korobov (9):
      PY3 array.array wants str in Python 2.x and 3.x - give it a str
      Update outdated comments in sklearn.hmm.
      PY3: fix exception syntax in tests/test_common.py
      PY3 fix test_cross_validation
      PY3 fix OneHotEncoder doctest ( "<type 'float'>" is "<class 'float'>" in Python 3.x)
      PY3 fix metaclasses. See #1829.
      ENH speed improvements in HMM
      TST Fixed test_pipeline_methods_preprocessing_svm: pca was unused
      Fixed typo in metrics.py

Miroslav Shubernetskiy (1):
      PY3 allow multiple base classes in six.with_metaclass

Naoki Orii (1):
      FIX issue #1457 KNeighbors should test that n_samples > 0

Nelle Varoquaux (62):
      DOC: small fix in the regression's score method documentation
      FIX make_classification now outputs integer labels
      DOC formatting (k_means)
      ENH - 3x speedup in the isotonic regression
      FIX gen_rst.py was something using an undefined variable
      Merge pull request #1886 from NelleV/DOX_fix
      Added sponsors to the about.rst page
      Spelling mistake
      DOC fix in the hierarchical clustering
      DOC Acknowledge sponsors for the Paris sprint
      DOC fixed small mistakes in the pls module
      Merge pull request #2140 from arjoly/ajoly-glouppe-sponsor
      DOC fix small mistakes
      DOC fixed some formatting in kernel approximation
      DOC fixed some formatting in the multiclass module
      Merge pull request #2146 from ianozsvald/clearer_iris_decision_surfaces
      Merge pull request #2163 from ianozsvald/fix_plot_forest_iris_docs
      ENH better error message when estimators don't specify their parameters in the signature.
      Merge pull request #2187 from FedericoV/non_negative_style
      Merge pull request #2195 from erg/bug-2189
      ENH added an option to do an isotonic regression on decreasing functions
      TEST: added a small test for fitting an isotonic regression on a decreasing function
      TEST tests the class instead of the function for the decreasing isotonic regression
      MAINT moved the pls file based module to a folder
      TEST fixing pls tests failing:
      MAINT Move the pls to the cca to a cross_decomposition module
      MAINT renamed pls to cross_decomposition in the documentation
      FIX the example plots of the pls module did not import pls methods from the correct module
      FIX removed the cca and pls modules
      FIX added the new module to the setup.py installation
      DOC improved docs/docstrings on cross_decomposition
      MAINT deprecated the pls module, moved CCA to cca_
      FIX init methods of ABCMeta class also need to be abstract
      FIX on py3k, we need explicit relative imports
      FIX missing deprecation release information.
      MAINT charset is deprecated in favor of encoding
      TST added tests for encoding/charset deprecation
      DOC better deprecation warning messages.
      TST better testing of the PLS module
      FIX PLSSVD now returns the correct number of components
      COSMIT small documentation tweaks
      DOC ignoring gen_rst's parsing errors
      Merge pull request #2280 from larsmans/randomsearch-scoring
      Merge pull request #2281 from ogrisel/improvements-to-setup-py
      DOC fixed the optional arguments
      FIX added some descriptions to each categories in the main webpage
      FIX spelling mistake
      FIX the css in the API
      ENH added the fork me ribbon to the website
      WEB added testimonials
      DOC fixed the previous/next button
      DOC fided the collapsable sidebar
      DOC dropdown menu works
      FIX minor edits on the website
      DOC fixed z-index on the website
      FIX website layout on small screens
      FIX improve display on small device
      DOC fix dropdown menu
      FIX backward compatibility was broken
      DOC added link from banner to example.
      DOC now building to html/stable
      DOC home always points to stable

Nicolas Trésegnie (38):
      DOC fix macports package name
      Add test for PatchExtractor (float value for max_patches)
      Fix float value support for max_patches in PatchExtractor
      Fix as_float_array behaviour when copy=True
      Add test of the as_float_array behaviour when copy=True
      Add a copy parameter to safe_asarray()
      Imp readability
      Missing value imputation
      Fix tests
      Fix tests + doc improvements + renaming
      Add test with default value of copy + doc improvements
      Imp readability
      Fix use of as_float_array
      pep8
      Imp variables names
      Del use of as_float_array + naming and documentation improvements
      Fix use of mask
      Fix import names
      Add pycharm files in .gitignore
      Imp splitting of preprocessing.py
      Imp splitting of test_preprocessing.py
      Del unused imports in preprocessing + pep8
      Fix imports
      Imp move OneHotEncoder to preprocessing/data.py
      pyflakes and pep8
      Fix self.statistics_ souldn't be set if axis==1
      Fix use of self
      Refactor loss_func and score_func warnings in grid_search
      Add score_overrides_loss to _deprecate_loss_and_score_funcs
      Add deprecation warnings in Ridge
      Add deprecation warnings in rfe
      Add catching of the deprecation warnings in rfe and ridge tests
      Refactor loss_func and score_func warnings in cross_validation + replacement in two examples
      Fix 'scoring' docstrings
      Imp documentation
      Fix tests
      Fix grid_search.py example
      Fix tests

Noel Dawe (102):
      implement AdaBoost
      use weighted mean in ClassifierMixin.score
      FIX: DecisionTreeRegressor.score
      FIX: import not used
      FIX: overlapping y-axis labels
      FIX: use generator instead of np.random
      rm doctest in make_gaussian_quantiles
      fix variable naming in weight_boosting
      FIX: TypeError for regressor
      FIX minor comment
      FIX: docs, code clean up, learn_rate -> learning_rate
      FIX: plot_adaboost_classification.py
      don't enforce DTYPE at the ensemble level
      DOCS: note generator behaviour in staged methods
      Make BaseWeightBoosting abstract and other misc changes
      revert changes to grid_search
      FIX: import
      revert implementation of sample weights in BaseWeightBoosting.staged_score
      revert a few spurious changes
      pep8 + pyflakes, use arrays for errors_ and weights_
      init weights_ to zeros and errors_ to ones
      add Hastie 10.2 example
      pep8
      implement SAMME.R algorithm
      update adaboost hastie example and weight_boosting tests
      use broadcasting
      combine real and discrete algorithms under one class
      DOC: AdaBoostClassifier real arg
      update example: fix histogram range
      Merge pull request #20 from glouppe/adaboost
      Merge pull request #21 from glouppe/adaboost
      update adaboost example: exposes instability
      displace predict_proba by 1e-10
      Merge pull request #22 from glouppe/adaboost
      FIX: adaboost predict_proba
      only boost positive sample weights
      FIX: only boost positive sample weights
      Merge pull request #23 from glouppe/adaboost
      FIX: negative and zero probabilities while boosting with SAMME.R
      FIX: doctest
      FIX: doctest and slightly larger displacement from zero probabilities (32 vs 64bit doctest instability)
      remove weighted_r2_score (leave for next PR scikit-learn#1574)
      revert spurious change in metrics.py
      FIX: use full decision tree in AdaBoost and fix title in plot_forest_iris.py
      DOC: add __doc__ to plot_adaboost_hastie_10_2.py
      FIX: reference format
      FIX: show decision boundary in plot_adaboost_classification.py
      FIX: refactor plot_adaboost_classification.py and add legend
      rename plot_adaboost_classification.py -> plot_adaboost_twoclass.py and add predict_twoclass method to AdaBoostClassifier
      FIX: only possible split sometimes creating children with negative or zero weight in the presence of negative sample weights
      FIX: improve multi-class AdaBoost example (rename to plot_adaboost_multiclass.py)
      add author
      typo
      use metrics module and pep8
      typo
      fix class ordering in two-class
      faster sample_weight initialization
      speed improvements to make_gaussian_quantiles
      even more speed improvements to make_gaussian_quantiles
      py3k
      DOC: note initialization of sample_weight if None
      factorize common sample_weight check
      Merge pull request #24 from glouppe/adaboost
      add decision_function and staged_decision_function and refactor some code
      Merge remote-tracking branch 'upstream/master' into treeweights
      Merge pull request #25 from glouppe/adaboost
      pep8
      Merge pull request #26 from glouppe/adaboost
      update adaboost regression example and use estimator_errors_
      rm n_estimators argument from predict methods
      DOC: fix docstring for make_gaussian_quantiles
      FIX: alpha=.5 and use more difficult dataset in two-class example. Add mean and cov arguments to make_gaussian_quantiles
      FIX: learning_rate default value consistency
      FIX: TypeError message if base_estimator does not support class probabilities
      FIX: comments from @ogrisel
      make learning_rate=1 default for classification
      only sum sample_weight once
      rm sphinx/docutils formatting in exception messages
      inline comment about learning_rate in hastie example
      add note about SAMME.R converging faster than SAMME
      add note about y coding construction
      add description of dataset in two-class example
      fix missing parenthesis in make_hastie_10_2 dataset
      Merge pull request #27 from glouppe/adaboost
      import pylab as pl
      remove check for fit_predict
      fix importance test and test both SAMME and SAMME.R algs
      don't show class B probabilities in two-class example
      two-class decision scores -> decision scores
      clarification on two-class decision scores plot
      explain decision scores in two-class example
      fix AdaBoost.R2 and update example
      DOC: loss_function
      fix failing tests
      fix failing doctest
      Merge pull request #28 from glouppe/adaboost
      API consistency with gradient boosting: loss_function -> loss
      Merge pull request #29 from glouppe/adaboost
      minor edits in docs
      DOC: notes about examples and minor edits
      make setup.py executable
      AdaBoost: use estimator weights in predict_proba

Norbert Crombach (1):
      Fix L2 regularization order in sgd_fast

Olivier Grisel (107):
      Update travis config to remove -qq flag for scipy
      P3K: support for py3k in dict_vectorizer module
      PY3: Fix stdout capture in graph lasso test
      P3K More python 2 / 3 compat in tree exports
      Merge pull request #1660 from rlmv/fe_tests
      P3K use six to have a python 2 & 3 compatible code base
      Merge pull request #1726 from agramfort/round_kfold
      Merge pull request #1730 from arjoly/doc-feature-selection
      Merge pull request #1741 from arjoly/metrics-fix-np-1.3
      PY3: Disable lib2to3
      PY3: fix urlopen in mldata and california housing loaders
      PY3: fix remaining cStringIO imports
      PY3: fix for string literals in datasets' test_base.py
      PY3: print function in coordinate descent doctest
      PY3: record is a kwarg argument for warnings.catch_warnings
      PY3: long is no longer a type in Python 3
      Merge pull request #1839 from amueller/dbscan_example
      FIX: use the mldata mock in docstring as well
      Merge pull request #1913 from Jim-Holmstroem/refactored_precision_recall_fscore_support_to_count_with_integer_type
      FIX: restore numpy 1.3.0 compat with np.divide fix
      FIX #2032, FIX #2033: ensure module names consistency with __all__
      Remove redundant test that was checked in by mistake
      FIX inconsistent cv_scores_ generation for randomized search and re-add example
      ENH: removed leftover condition to get a wider application of the import all consistency check
      Enforce n_folds >= 2 for k-fold cross-validation
      Merge pull request #2004 from oddskool/out-of-core-examples
      FIX: make doc auto-linking support any Unicode / UTF-8 content
      Make the out-of-core example plot work when launched by the sphinx extension
      FIX: do not print to many messages to stdout when generating the documentation
      PY3: New test for the get_params handling of deprecated attributes.
      Better status for the Py3 port
      Merge more Py3 fixes
      PY3: refcounting change introduced a regression on the use of resize in LARS
      FIX: pep8 and Py3 support in sklearn.neighbors.base
      FIX: Python 3 support for the neighbors doctests
      FIX: pep8 + Py3 fixes in test_dist_metrics
      FIX: pep8 and Py3 support in sklearn.neighbors.dist_metrics
      FIX: Py3 / pep8 fixes in test_ball_tree / test_kd_tree
      Update Python 3 support status
      Style
      More readable condition and more precise error message
      FIX: Py3 print statements to print functions
      Rename LabelBinarizer.multilabel to .multilabel_ + DOC
      WIP: partial fit for discrete naive Bayes models
      Remove the class_prior partial_fit param
      WIP: started to factorized the raw count collection
      Incrementally is useless now
      Add reference to the Manning text + restaure previous smoothing
      FIX shape issue when y has only one single class + some missing doc
      Factorize common classes checks in partial_fit implementations
      Add note on a possible future performance optimization
      Add a note on performance tradeoffs in the docstring of partial_fit
      More informative error message. Also CV now use integer indices by default now.
      Use floats everywhere to get rid of warnings when using sample_weight
      More input checks
      Better test name
      Remove redundant shape check already done by check_arrays
      Add missing test for sample weight with partial_fit + fix issue classes passed as a list instead of an array
      One more input check test
      Add missing test for deprecation warning
      Found a bug: add a failing test
      Use unique_labels more consistently in the multiclass model
      Fix broken partial_fit test
      Factorize label_binarize for binarizing a sequence of labels with fixed classes
      Add a new whats_new entry
      Add some doc for the new partial_fit method
      wording
      Avoid raising a deprecation warning on label_binarizer_.multilabel_
      Fix docstring and add some usage examples
      FIX: do not update feature_log_prob_ in _update_class_log_prior
      Add one more tests to check the performance on digits
      Make test_deprecated_fit_param pass under python 3 as well
      Address wording and typos identified in review
      Better parameterization for test_check_accuracy_on_digits
      Add a whitespace in parameter docstring item
      More accurate documentation for class_count_ and feature_count_
      Rename helper partial_fit function
      Merge pull request #2175 from ogrisel/nb-partial-fit
      Merge pull request #2228 from amueller/travis_virtualenv_stuff
      Trying to enable python 3.3 too.
      Update .travis.yml
      One more Python 3 fix in feature_extraction.rst
      Py3 fix
      More explicit tests in test_label_binarizer_column_y
      Catch expected warning in sklearn/tests/test_naive_bayes.py (part of #2274)
      Revert "Catch expected warning in sklearn/tests/test_naive_bayes.py (part of #2274)"
      FIX PY3: list and tuples cannot be compared in Python 3
      Py3: fix version comparison in imputation module
      Add supported python versions to the classifiers + fixes
      Sample compiler config for windows
      Force stdc++ link for the windows build
      Regenerate pairwise_fast.pyx with recent cython for windows build
      Fix atomics definitions under windows for sklearn._hmm.pyx
      typo
      Use extra_link_args for -lstdc++
      Ignore compiled shared library files generated in the source tree under windows
      Merge pull request #2293 from amueller/warning_input_shapes
      Rename cv_scores(_) back to grid_scores(_) to keep the name free for a future refactoring
      Merge pull request #2299 from ogrisel/grid-scores
      WIP: explicitly mark all base classes as ABC with abstractmethod inits
      Add concrete __init__ for LinearSVM
      Add concrete implementation for SGDClassifier
      Fixed a typo in a contributor's name
      Re-align the what's new file with the new ordering of items from master
      partial_fit for naive Bayes was done for 0.14-rc, not 0.11...
      Ignore the generated MANIFEST file
      Also clean the dist folder when calling make

Peter Prettenhofer (65):
      rename learn_rate -> learning_rate
      raise ValueError if len(y_true) is less than or equal to 1
      fix: map labels to {0, 1}
      fix: deviance computation in BinomialDeviance was wrong (ignored cases where y == 0) - thanks to ChrisBeaumont for reporting this issue
      raise ValueError if division through zero in LogOddsEstimator
      add loss function for gradient boosting binomial deviance
      pep8 and assert_equal instead of assert
      correct docstring
      Merge branch 'master' into gbrt-deviance-fix
      use unique from sklearn backports (return_inverse)
      Merge branch 'master' into gbrt-deviance-fix
      Merge branch 'master' into gbrt-deviance-fix
      decision_function forces dense output (in the case of sparse coef_)
      Merge branch 'master' into pr/1798
      get rid of ``rho`` in sgd documentation - has been replaced by ``l1_ratio``
      Merge pull request #1893 from dougalsutherland/sgd-docs
      corrected doctests after moving L2 penalty application in SGD
      Merge remote-tracking branch 'upstream/master' into pr/2016
      added SGD L2 fix to whatsnew
      fix: add missing str formatting operator
      enhanced (hopefully) DBScan documentation; killed some whitespace along the way...
      Merge remote-tracking branch 'upstream/master' into dbscan-doc-enh
      fix: needs_threshold not plural in repr
      removed min_density example - dropped param
      gbrt now works with new DecisionTree implementation
      import classes - now they work!
      fix: proper dtype for SIZE_t
      add GBRT to covertype benchmark
      added pxd to Manifest (to be included in source tarball)
      Merge remote-tracking branch 'upstream/master'
      add OOB improvement and set oob_score deprecated
      example for oob estimates in GBRT
      plot cv error as well
      rm print stmt
      rn: plt -> pl
      fix: oob_improvement_ with trailing _
      more docstrings
      cosmit: use train_test_split - tuned params for nice plot
      narrative documentation for oob improvement.
      more tests
      cosmit: better links and a note on efficiency using max_features
      comments
      cosmit: n -> n_samples
      cosmit: rs -> random_state
      more doc for OOB example
      use new style str formatting
      rearanged some code
      rn: ACC -> Accuracy
      rephrased max_features doc
      moved to new pyplot import
      more narrative documentation for oob in gbrt
      regression tests for oob_improvement_
      example doc string
      Merge branch 'gbrt-oob-improvement'
      covertype benchmark: use C-style input as default (most models require it as input)
      fix: use asserts from sklearn.utils.testing
      fix: python3.3 warning fix
      doc: hedge the use of OOB estimates
      Refactored verbose output in GBRT - output much more nice
      fix: newest numpy doesn't like all-indexing non-existing dimension (reported by erg #2233)
      Merge remote-tracking branch 'upstream/master'
      remove negative indices from neighbors cython code
      fix: check for impurity ties
      added 32bit 64bit equality test case
      adapt OOB regression test to change in tree module

Philippe Gervais (11):
      Style fixes
      [DOC] missing parameter description
      GraphLassoCV works with alphas given as list.
      Simplified GraphLassoCV code.
      Put back cov_init parameter in graph_lasso_path_
      Speed up some tests
      Removed unused import
      Added GraphLassoCV changes to whatsnew.rst
      [DOC] Corrected errors in clustering documentation
      [DOC] fixed a typo in an warning message.
      One more typo fixed

Rafael Cunha de Almeida (1):
      Only reassign centers if to_reassign.sum() > 1

Raul Garreta (5):
      PY3: used six.u to fix unicode variables in svmlight
      PY3: six.moves.cStringIO to fix StringIO import
      PY3: fix None comparison (when not in OS X) in test_k_means.py
      PY3: used six.moves.xrange to fix xrange
      PY3: used six.iteritems to fix dict iteritems in module pipeline.py

Rob Speer (6):
      Change 'charse_error' to 'charset_error' in load_files.
      Revise documentation about handling text and bytes.
      Add a documentation section about decoding text.
      Move the new "Decoding text files" doc section
      FIX Minor stuff in document_classification_20newsgroups output
      ENH Add filters on newsgroup text

Rob Zinkov (5):
      Adding support indices in svm for sparse matrices
      COSMIT PEP8
      Adding test to check support_ is equal in dense and sparse matrices
      COSMIT PEP8
      Recompiled base

Robert Layton (17):
      DOC improve mini-batch k-means narrative
      DOC: Replaced all BSD style licenses with "BSD 3 clause"
      Minimal spanning tree backported from scipy 0.13
      Added test
      Moved mst to a subfolder and added a README file
      Added new files (from previous commit)
      Merge pull request #2055 from jnothman/cv_refactor
      Merge pull request #2076 from pprett/dbscan-doc-enh
      Traversal in and tested. Next step is to remove references to old code
      Removed reference from spectral_clustering to old csgraph
      csgraph updated from hierarchical.py
      Removed actual _csgraph file, tests still all pass
      Turns out sparsetools wasn't needed either
      Missed a spot
      Reference to graph components updated in dev docs
      Two more spots. I think that's it
      Now that the folder has more than just mst in it, rename to sparsetools, which should help with referencing it.

Robert Marchman (13):
      test case for unfitted idf vector
      raise ValueError for unfitted idf vector
      FIX docstring deletions
      ADD test coverage for _check_stop_list
      FIX comment typo
      ADD test cases to fill out VectorizerMixin coverage
      ADD another VectorizerMixin test
      ADD test for get_feature_names
      ADD test for tfidf fit with incompatible n_features
      ADD test for TfidfVectorizer attribute setters
      MV Mixin tests to CountVectorizer tests
      RM CV import
      MV _check_stop_list tests to CV get_stop_words

Robert McGibbon (3):
      fix the kwarg name
      updated the .c file
      remade the cython with 0.18

Rolando Espinoza La fuente (1):
      DOC typo: Pereptron -> Perceptron.

Roman Sinayev (3):
      ENH Rewrote CountVectorizer fit_transform to be ~40% faster
      ENH refactor and further speed up CountVectorizer
      ENH speed up TfidfTransformer using spdiags

Seamus Abshere (1):
      ENH reduce size of files produced by dump_svmlight_file

Sergey Feldman (1):
      Adding covariance regularization to QDA

Sergey Karayev (2):
      fixing bug in linear_model.SGDClassifier for multi-class warm start
      removing accidental space

Sergio Medina (1):
      Corrected a few things on the Mutual Information doc pages.

Stefano Lattarini (1):
      COSMIT various typofixes

Steve Koch (1):
      Update hmm.rst

Steven De Gryze (9):
      PY3: fixed basestring in crossvalidation.py
      PY3: use b() convenience function for string literals
      PY3: ensuring file stream is read as binary
      PY3: convert string literal to bytes using six in cython file
      replacing numpy array with range for use in random.sample
      PY3: changing None to 0 to ensure comparability in py3
      PY3 fixing utf8 comments in svm through try/except and six.b
      PY3: forcing execution of map by using tosequence
      PY3 fix comparison of ndarray and string

Sturla Molden (1):
      Update typedefs.pxd with correct ITYPECODE

Szabo Roland (3):
      ENH Added custom kernels to SpectralClustering
      BUG Add lambda_ attribute to ARDRegression after fit
      DOC Add labels and some explanation to confusion matrix example

Tadej Janež (10):
      Removed an unnecessary if statement in KFold __iter__ method.
      Improved the test that checks the balance of sizes of folds returned by KFold.
      DOC Corrected the docstring of KFold about the sizes of the folds.
      COSMIT Moved the test_roc_curve_one_label test where other ROC curve tests are.
      FIX KFold should return the same result when indices=True and when indices=False.
      ENH Function auc_score should throw an error when y_true doesn't contain two unique class values.
      ENH optimizations in sklearn.cross_validation
      FIX Moved copying of labels in LeaveOneLabelOut and LeavePLabelOut to __init__.
      TST Added test that checks if LeaveOneLabelOut and LeavePLabelOut work normally if the labels variable is changed before calling __iter__.
      DOC Fixed doc test to work with the fixed versions of LeaveOneLabelOut and LeavePLabelOut.

Thomas Jarosch (1):
      BUG delete/delete[] error in Liblinear

Vlad Niculae (71):
      FIX: variable naming inconsistency in NMF
      DOC FIX: multi-target linear model attribute shapes
      DOC spelling and clarification
      Make callable svc test more robust for MacOSX.
      Added RBM to whats_new.rst
      DOC Added skeleton for RBM documentation
      ENH Rename RestrictedBolzmannMachine to BernoulliRBM
      FIX: make BernoulliRBM doctest pass
      FIX: BernoulliRBM check random state in fit, not in init
      FIX: validation in `BernoulliRBM.transform`
      DOC: first attempt at RBM documentation
      Link to RBM docs from the unsupervised toctree
      FIX: uneven RBM image
      DOC: PCD details and references
      Fix typos in example
      PEP8 and indentation
      DOC add plot and example to docs
      DOC rewrite BernoulliRBM example description
      Set seed through params, not globally
      FIX handling of random state, hide some of API
      Pep8 example
      Update example params by grid search, and docstring
      One space after dot
      DOCFIX neural networks module
      DOCFIX spacing and clarification in RBM docstring
      More stable implementation of logistic function and its derivative by @fabianp
      Use gen_even_slices instead of homebaked code
      ENH Add fast and stable logistic sigmoid to utils and RBM
      ENH Support sparse input in RBMs
      ENH Prevent memory copying in RBM's _fit
      Do not touch uncopied memory
      Nudge images using convolve, slower but more readable
      Clarify narrative docs
      Clarify and python3 RBM example
      Periods and other docstring issues
      Remove redundant test
      Python3 support in RBM
      TST RBM smoke-test verbosity
      FIX missing class attribute in ICA. Common test was failing
      FIX: fastica function dictionary default value
      Deprecate FastICA.sources_
      TEST remove deprecated stuff from fastica tests
      Document the deprecation
      FIX bug in test
      Clean up and rename Hungarian algorithm
      Clarify and clean up example
      Remove print in Hungarian tests
      Consistency for floats in consensus score
      Add warning in private _Hungarian docstring just in case
      ENH make spectral clustering test more stable to random seed
      ENH add return_path in orthogonal matching pursuit
      TEST for omp path feature
      ENH OrthogonalMatchingPursuitCV estimator
      FIX respect conventions in OMP init
      FIX OrthogonalMatchingPursuit normalized twice
      Use projected gradient solver in transform to support sparse matrices
      Use same parameters when solving the transform
      Use scipy.nnls.optimize for dense data
      Add failing test for libsvm random state proba
      FIX support random state in libsvm
      DOC document changes in LIBSVM_CHANGES
      DOC update docstrings to reflect libsvm random_state
      Fix libsvm seed when predict_proba in tests and examples
      Clarify and make libsvm random seed more consistent
      Comment predict params in libsvm
      DOC reference and rename cross decomposition module
      FIX raise tolerance in svm predict_proba test
      Make common PLS tests more stable
      FIX for MSVC inline fmin, fmax and log2
      FIX for MSVC inline fmax in dist_metrics
      Add LibSVM random state to changelog

Yann N. Dauphin (25):
      ENH added Restricted Boltzmann machines
      30% speed-up thanks to in-place binomial
      ENH 12% RBM speedup with ingenious ordering of operations
      rename h_samples to h_samples_
      added URI for RBM reference
      improved docstring for transform
      renamed _sigmoid to _logistic_sigmoid
      use double backquotes around equations
      logistic_sigmoid moved to function
      transposed components_, no performance penalty
      only compute pseudolikelihood if verbose=True
      more accurate pseudo-likelihood
      use iteration terminology instead of epochs in RBM
      default n_components from 1024 to 256
      clarify some method names (ex: mean_h -> mean_hiddens)
      added epoch time
      ENH RBM example
      switched to digits
      moved rbms to neural_networks module
      add tests for rbm
      trim whitespace
      use train_test_split
      neural_networks -> neural_network
      ENH rename n_particles to batch_size in RBM
      TST added more RBM tests

Yannick Schwartz (2):
      BUG: set random state in LogisticRegression
      Update multiclass/multilabel documentation

Yaroslav Halchenko (7):
      BF: explicitly mark train_test_split as not the one for nosetesting
      Merge commit '0.14a1-20-gc9ba2c3' into releases
      Merge commit '0.14a1-239-g0872592' into dfsg
      Merge branch 'dfsg' into debian
      changelog entry
      debian/control - python-imaing to build-depends (for documentation) and removed not needed XS-DM-Upload-Allowed
      Let's upload to experimental for testing

draix (1):
      PY3: replaced izip

hrishikeshio (1):
      DOC dev guide: deprecation

jamestwebber (2):
      Update coordinate_descent.py
      Fixed precompute issue (again) in ElasticNet and enet_path

nzer0 (1):
      Documentation ERROR: mixture.DPGMM.precs_

sergeyf (8):
      Update qda.py
      Update qda.py
      Missed a space!
      Updating to ensure pep8 compliaance
      reg_param is a float
      Update qda.py
      Update test_qda.py
      Update qda.py

syhw (10):
      nudging the digits dataset for BernouilliRBM example
      TST added a 'fit [[0],[1]] + gibbs sample it' test for RBMs
      replaced test_gibbs by a smoke test for NaNs
      check for pseudo_likelihood clipping
      COSMIT refactoring rbm
      RBM example now verbose
      squeezing logistic_sigmoid result only on 1D arrays
      adding a test for sparse matrices in RBM
      changing free_energy to private in RBM
      added neural_network to setup

uber (1):
      example yahoo stock issue fix

unknown (1):
      changed wording in linear model docs about Normalized. It was frustrating me haha

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