[scikit-learn] annotated tag debian/0.13-1 created (now e02df25)
Andreas Tille
tille at debian.org
Wed Dec 28 13:10:59 UTC 2016
This is an automated email from the git hooks/post-receive script.
tille pushed a change to annotated tag debian/0.13-1
in repository scikit-learn.
at e02df25 (tag)
tagging 351a30ba09fb07a709baa62b60377f627b1f5dcc (commit)
replaces debian/0.12.1-1
tagged by Yaroslav Halchenko
on Wed Jan 23 14:03:14 2013 -0500
- Log -----------------------------------------------------------------
Debian release 0.13-1
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Alejandro Weinstein (1):
Fix link to plot_lda_qda example.
Alexandre Abraham (3):
Fix typos
BUG: Fix path in doc cleaning
Merge branch 'master' of https://github.com/jaquesgrobler/scikit-learn into fix_doc_clean
Alexandre Gramfort (38):
DOC : fix rho=1 is L1 penalty #1139
fix failing test
TST : use nose assert_true and not python assert
ENH : proper IsotonicRegression model + example + test
remove support for extrapolation
FIX : for test_common sparse support
pep8
adding my name in IR example
ENH : finish addressing @GaelVaroquaux comments + improve coverage + add linear regression to example
typo
FIX : fix LLE test (don't ask me why...)
misc
DOC : avoid mentioning ElasticNet in Lasso.fit docstring
Merge pull request #1223 from ibayer/master
ENH : cleanup FactorAnalysis object
API : rename psi to noise_variance + some cleanup in FA
TST : add test that FA log like increases over iterations
add Bishop's book to refs in FA
update what's new with FactorAnalysis
DOC : adding FactorAnalysis to classes.rst
FIX : fix application example due to API change
FIX : missing import warnings
typo
typos
DOC: typos in ensemble.rst
DOC: typos in ensemble.rst
FIX : clean test + pep8 + reply fix to the code
API : move isotonic regression out of linear_model
DOC : fix move of isotonic in doc + examples
TST : use assert_true and not assert in test
Merge pull request #1483 from aweinstein/fix_doc_example
Merge pull request #1504 from NelleV/isotonic
Merge pull request #1505 from NelleV/mds
DOC : add doctring in plot_lasso_and_elasticnet.py
DOC: adding Bishop as ref for ARD
Merge pull request #1577 from ApproximateIdentity/n_jobs-documentation
Merge pull request #1578 from zaxtax/elastic_documentation
DOC : missing alpha doc in LassoLars
Alexandre Passos (1):
dpgmm: setting the weights to something reasonable
Andreas Mueller (367):
COSMIT typo, thanks @ogrisel
DOC add people and commits do whatsnew
MISC starting 0.13 cycle
ENH more robust transformer testing.... don't ask why that came up
ENH address issue 1028: clone estimator in RFE
ENH issue 1115: grid search support for rfe via ``estimator_params``
ENH fixed bug in sparse RFECV, fixed bug in RFECV init (step was always 1), added decision_function and predict_proba to RFE and RFECV
MISC rfe outputs loss, not score
FIX typo
add y to tfidf vectorizer
WEBSITE updated logo, changed scikits-learn to scikit-learn.
ENH remove some deprecated parameters / functions /estimators
FIX remove test for deprecated parameter.
Example: added a pretty PCA 3D plot of iris, as this dataset is used in so many examples.
ENH minore example beautification
DOC fixed default value of ``compute_importance`` in DecisionTreeClassifier docstring.
DOC typo in ElasticNet docstring
DOC add isotonic regression to References (even if we move it soon), also OCD.
FIX error in error message ^^ closes #1155.
ENH fix percentile tiebreaking, add warning
DOC document attributes scores_ and pvalues_ in feature selection docstrings, some superficial cleanup.
DOC somewhat improved feature selection example
ENH in NMF only use svd initialization by default if n_components < n_features.
FIX fixed typo in code, added smoke test.
COSMIT remove unused imports
DOC added Conrad Lee's PR to whatsnew
COSMIT pep8
FIX unicode support in count vectorizer. Closes #1098.
FIX docstring for count vectorizer. Sorry about that.
COSMIT remove unused import
ENH add MinMaxScaler, #1111
ENH do normalization in single pass over data
DOC added missing docstrings
ENH rename Scaler to StandardScaler everywhere
COSMIT pep8
DOC remove sparse support from docstring as there is none. Also cosmit on docstrings.
ENH add FeatureStacker estimator
ENH add feature stacker example
COSMIT + DOC more dosctrings, minor improvements
ENH implement get_feature_names
TST added tests, fix feature names.
ENH add parallel fit and transform with joblib.
ENH add transformer weights
TST add test for feature weights in feature stacker
DOC move example (there is nothing to plot) and add some text
MISC renaming FeatureStacker to FeatureUnion, adding docs
DOC added FeatureUnion to whatsnew.
ENH remove deprecated sparse SVM class from cross-validation test.
COSMIT pep8
FIX bug in pipeline.inverse_transform, improve coverage.
ENH support for string labels in Neighbors classifiers
ENH rename ``_classes`` to ``classes_``, fix outlier labeling, remove unnecessary mapping to indices.
COSMIT reuse variable name
ENH added non-regression test
COSMIT removed unused import
FIX np.unique doesn't have return_inverse keyword, use backport from utils.
ENH slightly better error message for robust covariance
enh even better error message
ENH make multi-class more robust in discovering scoring functions
ENH in all_estimators, skip testing modules. They have dummies.
TST improve test-coverage in base, remove unreachable code-path
COSMIT pep8
DOC added whatsnew entry for mutual info fix and faster confusion matrix.
ENH rename k to n_folds and n_bootstraps to n_iterations
DOC cleanup some docstrings (not scipy standard yet)
ENH set n_fold default to 3, rename k to n_fold in all doctests, docs, and examples
COSMIT rename n_iterations to n_iter in cross_validation
MISC renamed n_iterations to n_iter in all other places.
DOC added changes / renames to whatsnew
ENH rewrite K-Means m-step as loop over samples, cythonize.
ENH separate sparse and dense case, cythonize further.
ENH fix int type in kmeans
ENH fix kmeans for old numpy (bincount minlength)
FIX also the other function in kmeans. whoops
FIX bincount mess I made in kmeans.
ENH rename rho to l1_ratio in ElasticNet and friends
ENH rename rho in SGD
ENH address @agramfort's comments, fix some doctests
DOC add changes to whatsnew.
ENH simplify as suggested by @larsmans.
FIX for len(result) > minlength
DOC tried to clarify meaning of l1_ratio in whatsnew
ENH remove some unreachable code from gridsearch
ENH sparse matrix support in randomized logistic regression
FIX doctests for max_iter
FIX two more docstrings. Sorry.
FIX seed liblinear using srand. Fixes issue #919.
ENH add random seed to logistic regression
ENH don't use deprecated interface in PPCA & cosmit
REL put myself as contact / maintainer, fixed url
FIX rebase mishap
DOC small example / doctest for kernel approximation.
DOC typo in whatsnew
DOC more typos in whatsnew.
ENH use the numbers module introduced in Python 2.6 to check for number types.
ENH added OneHotEncoder
DOC minor fixes / typos. Thanks @larsmans.
ENH user-specified dtype, defaults to np.float, nicer numpy stuff :)
TST skip test in common_tests, reach 100% coverage on new code.
DOC more typos omg. comment about automatically inferring maximum values.
ENH better example.
enh masking out zero features
TST fixed doctests, added more tests. Still 100% line coverage :)
ENH removed ``remove_zeros`` parameter.
DOC more extensive classifier comparision on synthetic datasets
ENH more noise, cross-validated parameters.
ENH train/test split, plot accuracy, make plot pretty.
ENH simplify circles dataset generator, make classes balanced.
FIX typo in dataset generation
ENH I'm more happy with the last example now....
FIX adjust gamma in kernelPCA tests to fit slightly modified circles with balanced classes.
FIX HMM test failures
ENH used asarray to avoid copy
COSMIT pep8
enh: add code analysis target to makefile
FIX small bug in feature selection error message.
COSMIT do less deprecated things.
FIX revert useless change.
DOC warn about parallel k-means on OS X.
ENH minor improvements in testing, new utility function for safely setting random states.
FIX cross_val_score now honors ``_pairwise``
DOC added my last PR (cross_val_score fix) to whatsnew
WEB color fix for link headlines
DOC document callable kernels in SVM docstring.
DOC add user guide for MinMaxScaler
COSMIT in mean shift docs
FIX hotfix for NMF sparsity problem
FIX dirty fix for expected mutual info in cython.
ENH added OneHotEncoder
DOC minor fixes / typos. Thanks @larsmans.
ENH user-specified dtype, defaults to np.float, nicer numpy stuff :)
TST skip test in common_tests, reach 100% coverage on new code.
DOC more typos omg. comment about automatically inferring maximum values.
ENH better example.
enh masking out zero features
TST fixed doctests, added more tests. Still 100% line coverage :)
ENH removed ``remove_zeros`` parameter.
Merge branch 'larsmans_pr' into one_hot_encoder
COSMIT pep8
DOC corrected whatsnew.rst. Thanks @ogrisel.
ENH check in all classifiers in fit and predict that input is finite. inspired by #1027.
ENH add checks for clustering, regressors, transformers
FIX revert old behavior, all tests work :)
MISC address Gael's comments
DOC added comment about default for n_nonzero_coefs.
COSMIT pep8
ENH added check for non-negative input.
Merge pull request #1279 from amueller/one_hot_encoder
FIX don't use pl.subplots.
ENH adding "apply" to random forests
ENH add RandomHashingForest estimator.
ENH added docs, example and tests.
DOC Some narrative documentation for Random Forest Hashing.
FIX for sparse matrix in RandomForestHasher
ENH refactor inheritance structure.
ENH use random regression task to avoid memory overhead of n_sample classes.
ENH Added Example
DOC added references
MISC renamed RandomForestHasher to RandomForestEmbedding
MISC don't use pl.subplots, fix typo
MISC rename plot_random_forest_hasher to plot_random_forest_embedding
ENH fix plot in docs. thanks @ppret.
DOC forgotten rename
DOC fixed links in whatsnew.
DOC added dump_svmlight_file to the references
DOC improve MinMaxScaler narrative docs.
DOC added new precision_recall_curve to whatsnew
DOC fix some layout on the "presentations" page, add Jake's resent PyData NYC tutorial.
MISC rename RandomForestEmbedding to RandomTreesEmbedding
COSMIT don't do deprecated things in test (hmm)
COSMIT pep8, removing unused imports and recommend ``toarray`` instead of ``todense``
ENH make sparse svm test more robust, catch warning on deprecated class
ENH use blobs instead of iris in the common classifier tests. Iris has duplicat datapoints which raises annoying neighbors warnings.
ENH slight cleanup in common tests, less warnings.
ENH Check what ``__init__`` does in test_common
FIX messed up memorizing gmms parameter in GMMHMM before.
DOC added comment to test.
DOC explain what the test is doing.
ENH add chi2 and exponentiated chi2 kernel.
FIX add generated c file
DOC add chi2_kernel and exponential_chi2_kernel references.
TST added a test for chi2 and exponential chi2 kernel.
FIX input validation, test chi2 in pairwise function, add reference.
ENH fused types for chi2_kernel
ENH renamed chi2 to additive_chi2 and exponential_chi2 to chi2, as usually the exponential version is meant with "chi2"
DOC updated whatsnew
DOC cleared up difference to AdditiveChi2Sampler, added some "see also"s
DOC added stuff about chi2 kernel to narrative docs
FIX typo bug, more tests. Still more tests coming right up!
DOC added "precomputed" variant to docs.
TST 100% line coverage
ENH explicit check for zero denominator
ENH address @ogrisel's comments.
ENH addressed @kuantkid's comments. Also add myself to pairwise.py authors.
FIX import assert_greater from testing module
FIX csr conversion in amg code in spectral embedding
Merge pull request #1428 from tnunes/feature_union_fit_transform
ENH cleanup tests, lower tolerance
COSMIT pep8
FIX and test deprecated import of spectral_embedding from cluster
TST better test-coverage in clustering module
COSMIT in cross-validation tests
FIX random state in test by @briancheung. Thanks
TST better coverage in dict learning and cross validation
TST better coverage in preprocessing module
DOC add matplotlib version requirement, rephrase
COSMIT Mean Shift docs.
Merge pull request #1441 from kuantkid/fix_spectral_test
COSMIT some fixes in whatsnew rst
ENH Nystroem kernel approxmation
ENH renamed class NystromKernelApproximation to Nystrom (it is in the kernel_approximation module). Also improvements to example docstring
DOC docstrings for Nystroem.
ENH cosmit, gamma defaults do None, not 0. address some of @mblondel's comments.
ENH tests for Nystrom, check that n_components is smaller than n_samples.
DOC narrative doc for Nystroem.
DOC updated whatsnew with Nystroem.
ENH don't import * in utils __init__.py
TST better coverage for GridSearchCV, test unsupervised algorithm.
TST better test-coverage for image patch extraction.
TST better coverage in kernel_approximation
ENH input validation only in ``fit`` in LassoLarsIC, check that error is raised.
TST document and test verbosity parameter of lars_path
TST some more tests for SGDClassifier input validation
ENH / TST better coverage of supervised clustering metrics, slight cleanup
DOC make unit test requirements a bit stricter. 80% is sub-par with current code-base
COSMIT pep8
COSMIT renaming chunk_size to batch_size in MiniBatchDictionaryLearning and MiniBatchSparsePCA
DOC add rename to whatsnew
cosmit pep8
FIX GridSearchCV on lists that I broke in 8b3e4d06c05ac82130176161404f0434b74fe2c7
ENH added test, started on cross_val_score
ENH allow lists in check_arrays
ENH make cross_val_score work, some refactoring in GridSearchCV
ENH consistency: stuff is not an array if it doesn't have ``shape``.
TST GridSearchCV raises ValueError when precomputed kernels are not matrices.
ENH Simplify estimator type checking in GridSearchCV.
FIX don't use assert_allclose. It is not supported in numpy 1.3
COSMIT pep8
COSMIT featuers -> features typo
COSMIT PEP8
COSMIT pep8
DOC add version when setting parameters in fit will be removed to docstring
FIX typo / bug in test_common that ignored the first init parameter.
TST make test more stable.
ENH slight improvement of common tests.
DOC slight cosmit in metrics docstrings.
FIX i should trust my past self a bit more
ENH use an array instead of a dict in RFECV
Cosmit pep8
TST a little more coverage in unsupervised metrics.
ENH clean up redundant code in pairwise
ENH more test coverage in pairwise distances
FIX more robust test for silhouette score
DOC classifier comparison: plot data without decision boundary first, better (imho) color scheme.
DOC add Nystroem kernel approximation to the references
FIX stupid mistake
COSMIT pep8
COSMIT Typo
COSMIT update warning, pep8
ENH refactoring class weights for SVM and SGD
TST all classifiers now have "classes_". adjust test_common.
ENH remove class_weight_label from python side of SVM
ENH remove class_weight_label from sparse svm
TST move test of "classes_" to the appropriate test in "test_common".
FIX remaining doctests
DOC docstring for compute_class_weight
ENH remove class_weight_label from LibLinear python side.
ENH removed unused old function
TST fix import in test
ENH addressed @ogrisel's comments.
DOC changed docstring to be more clear.
ENH documented changes for SVC classes_ changes.
ENH move utility function into dedicated file, not __init__.py
TST start on testing consistent class weights
ENH nu-SVC doesn't support class_weights
FIX liblinear class weight in binary case, robust testing.
cosmit whitespace
DOC add comment in liblinear
TST better test for class weights (that actually tests something)
ENH test automatic setting of class weights in common test
TST skip RidgeClassifier in class weight test for the moment
DOC added fix to whatsnew.
FIX don't test auto in ridge classifier as it is not supported currently
FIX tests for auto class weights
DOC more concrete whatsnew
FIX skip tests for naive bayes for the moment.
DOC made myself contact for authors, changed my website to blog.
TST add cosine_kernel to kernel tests, pep8
ENH lazy import of metrics in base, not preprocessing in metrics.
ENH document attributes in QDA and LDA, rename to adhere to sklearn conventions.
DOC fix shape of coef_ for LDA.
TST somewhat hacky fix for tests on image loading.
ENH more logical behavior, better docstring, tests
FIX do checks even if allow_lists
DOC try to be as clear as possible.
ENH cleanup in check_pairwise_arrays, raise error on sparse input in chi2_kernel and manhattan_distance
COSMIT doc formating
DOC updated whatsnew
ENH added class_weight to Naive Bayes docs.
FIX random seed in FastICA testing.
DOC fix docstring of GMM
ENH rename proximity to dissimilarity
ENH common test that set_params returns self.
COSMIT remove empty file
DOC more accurate comment in class weight computation
FIX make sure laplacian in spectral clustering test is really PSD
DOC add recall_score to new classification metrics listing
DOC document gamma in chi2_kernel.
TST add common test to check if estimators overwrite their init params
ENH use only a few samples in test.
FIX in tree and ensemble: don't overwrite random state in fit.
FIX don't overwrite random_state in fit in EllipticEnvelope
FIX don't modify random_state in clustering algorithms.
ENH make code more clear: MiniBatchKMeans only uses random_state in first run of partial_fit.
FIX in ward: don't overwrite n_components.
FIX remaining parameter issues in GradientBoosting
TST took the safty off the tests ;)
Merge pull request #1582 from ApproximateIdentity/doc-n_jobs-parallel
DOC some sphinx fixes
DOC fix in mds example (new interface)
DOC mds example: suppress warning for explicit initialization
DOC don't use deprecated parameter rho in the lasso / enet examples
COSMIT typos in hierarchical clustering warning
DOC more sphinx fixes
EXAMPLE don't use deprecated interface in lasso model selection
COSMIT pep8 in examples
COSMIT pep8
DOC more sphinx fixes
FIX sort indices in CSR matrix for SVM
TST add regression tests for Alex' fix.
ENH rename cosine_kernel to cosine_similarity. Also make the test actually do something.
DOC fixed problem in citations in spectral_embedding
COSMIT typos
ENH don't use deprecated class_prior fit parameter for NB in test
ENH in spectral_embedding: do input validation before anything else
TST in testing deprecated load_filenames catch deprecation warning
TST catch expected warning in sparse coordinate descent test.
DOC cosmit fix column span alignment errors.
FIX example uses old parameter name
COMPatibility more careful deprecation of mode and k in SpectralClustering
COMP more careful deprecation of seed in SGDClassifier
COMP add deprecated property rho to ElasticNet
COMP keep seed as init parameter of Perceptron, only deprecate
COMP add deprecated ``labels_`` property to LinearSVC
FIX deprecated properties in ElasticNet
COMP in SVC rename self.label_ to self._label (it is redunant now but I don't want to refactor the rest of the day) and add a deprecated property label_, that points to classes_.
FIX in Perceptron and doctest
FIX in common tests: don't test init parameters that are deprecated. They might be changed.
FIX some doctests for SGD
COSMIT typo thanks @jaquesgrobler
ENH don't return deprecated parameters by get_params.
FIX typo in spectral clustering deprecation
TST catch deprecation warning when testing SVC label_ attribute, also test new classes_ attribute.
DOC reorganized whatsnew a bit, put new estimators on top.
DOC added user guide links to all estimators on the whatsnew page
DOC some more fixes for whatsnew
EXAMPLES add header to hash_vs_dict_vectorizer.py - otherwise it won't show in the html docs.
COSMIT pep8
ENH undo renaming of class_prior to class_weight in naive bayes
Merge pull request #1529 from vene/lgamma_port
DOC some more minor fixes to syntax / links
DOC fix indentation typo
DOC added commit counts for 0.13 to whatsnew, added website for Rob Zinkov aka zxtx
COSMIT pep8
DOC updated commit counts.
REL changed version to 0.13 everywhere.
website: fix for survey bar
Andrew Winterman (18):
implemented predict_proba for OneVsRestClassifier
forgot an except clause
removed unnecessary repeat
corrected doc for predic_proba, also caught few errors.
wrote test_ovr_predic_proba method
divided test for predict_proba into two functions
removed check for predict_proba method.
[pep 257](http://www.python.org/dev/peps/pep-0257/) and and other doc improvements.
corrected bad test in test_multiclass
Flake8 Corrections made
spell checked
Spelling is checked, passes Flake8 without errors.
added backtick around self.classes_ in multiclass.py
changed n_folds > min_labels error to warning
removed tests for the old error.
added test for warning. Added warning category
removed a carriage return in warning message
added space between # and text
Anze (5):
P3K: Fixed imports.
P3K: Cannot compare list to tuple.
Replaced use of deprecated method.
P3K: Changed StringIO to BytesIO to fix a failing test.
P3K: Fix build for py3k + pip.
ApproximateIdentity (4):
Changed a minus sign to a plus sign in the documentation of n_jobs in some files.
Changed minus sign to plus.
Added n_jobs to multiclass.py
Revisions due to previous pull request.
Arnaud Joly (143):
ENH add random-seed args
Call DecisionTreeRegressor instead of Tree
COSMIT Remove duplicated assignement
Use the check_input argument
DOC : add description of check_input args
DOC explain parameter estimators_
DOC explain parameter estimators_ (2)
ENH Move parameter checking to fit
COSMIT
FIX casting bug
ENH preserver contiguous property
COSMIT
DOC describe reasons for reshape
PEP8
FIX: perform transition from tree to DecisionTreeRegressor
FIX feature importance computation + Enable smoke test of feature importances
Update whats new
ENH add author
COSMIT use sklearn.utils.testing
ENH Let the user decide the number of random projections
Clean random_dot features
Clean random_dot features (2)
Clean random_dot features (3)
Clean random_dot features (3)
ENH let the user decide density between 0 and 1
COSMIT
ENH Strenghtens the input checking
ENH Add gaussian projeciton + refactor sparse random matrix to reuse code
ENH add more tests with wrong input
ENH add warning when user ask n_components > n_features
DOC: correct doc
ENH add more tests
Update doctests
ENH cosmit naming consistency
FIX renaming bug
COSMIT
WIP: add benchmark for random_projection module
ENH finish benchmark
Typo
ENH optim sparse bernouilli matrix
FIX example import (name changed)
FIX: argumetn passing selection of sparse/dense matrix
ENH assert_raise_message check for substring existence instead of equality
ENH add two test to check proper transformation matrix
PEP 8 + PEP257
DOC improve dev doc on reservoir sampling
COSMIT + ENH better handle dense bernouilli random matrix
FIX: make test_commons succed with random_projection
DOC removed unrelevant paragraph(s)
ENH add implementation choice for sample_int
ENH add various sampling without replacement algorithm
Typo
TST: Add tests for every sampling algorithm + DOC: improved doc
DOC: fix mistake in the doc + ADD benchmarking script
ENH Rename sample_int to sample_without_replacement
DOC + ENH: minor add in doc + set correct default
FIX: broken import
FIX typo mistakes + ENH change default behavior to speed the bench with Gaussian random projection
ENH Add allclose to sklearn.testing
ENH improve naming consistency
PEP8
COSMIT
DOC + typo
DOC set narrative doc for random projection
FIX: broken test due to typo correction
DOC minor improvements
DOC mainly switch from .\n:: to ::
FIX typo mistakes
DOC improve name in example
DOC Separate the jl example from references
ENH Add jl lemma figure to random_projection.rst
COSMIT (typo, doc, simplify code)
pep8
Typo
DOC typo in narrative doc
DOC fix typo in filename
DOC clarification
ENH flatten random_projection module + add sklearn.utils.random
ENH refactor matrix generation BaseRandomProjectiona and subclass
DOC improve layout (url)
Make the JL / RP example use the digits dataset by default
FIX broken import
pep257 + COSMIT: naming consistency
COSMIT
COSMIT
Remove unused line
DOC improve doc for jl lemma function
typo
ENH Rename Bernoulli random projection to sparse random projection
ENH Rename Bernoulli random projection to sparse random projection
DOC add see also
pep8
COSMIT make everything use the common interface
DOC improve + fix mistakes + TST added
ENH Simplify assert_raise_message + TST add them
DOC add utitilies to the doc
DOC + FIX density to Ping and al. recommandation
ENH make jl lemma work even with non numpy array
DOC add default values
ENH Add support for multioutput metrics
DOC add narrative doc for regression metrics
Update what's new
TST check that ValueError is raised when the number of output differ
ENH add mean absolute error
DOC cosmit alphabet order of classification metric in ref
DOC typo
ENH add multioutput support for dummy estimator
DOC instance attributes + TST: do not record warning
DOC typo
ENH preserve output ndim
COSMIT reorganized functions in the module
DOC add narrative overall description of classification metrics
DOC add hinge loss narrative doc
DOC Set reference links in the doc
DOC add narrative doc on zero_one loss metric
DOC add narrative doc on zero_one_score
DOC add narrative doc for precision, recall and fbeta measures
DOC add narrative doc on roc curve
DOC add narrative doc on auc and average precision
DOC add narrative doc on matthews_corrcoef
DOC add narrative doc for explained variance
DOC add reference to multioutput metrics in regression
DOC add link to clustering metrics
Update what's new
ENH renamed metrics.zero_one to metrics.zero_one_loss
ENH rename zero_loss_score to accuracy_score
ENH ClassifierMixin use a metrics from sklearn.metrics
DOC add classification_report to the narrative doc
DOC typo and mistakes
DOC comment from @amueller + several minor improvements
TST + DOC add many examples on sklearn.metrics
DOC typo + minor improvements
DOC remove redundant comment
DOC better example with dummy estimator + link to appropriate reference
ENH use deprecated decorator
FIX DOC missing default behavior change
DOC COSMIT pretty math
DOC clarification of api change
FIX catch deprecation warning
COSMIT (don't change anything see sparse_random_matrix)
Typo
FIX add doctest ellipsis
FIX doctests dtype
Aymeric Masurelle (19):
FIX : pass random_state to kmeans in gmm.fit
FIX : add condition pos_label!=None for multiclass purpose in metrics.precision_recall_fscore_support
TEST : add a test, test_precision_recall_f1_score_multiclass_break(), that breaks with current master and now works
Change metrics.py as before and shorten test (test_precision_recall_f1_score_multiclass_break() in test_metrics.py) to show where it breaks
ADD : cosinus kernel calculation in metrics/pairwise.py
add cos_kernel in help of decomposition/kernel_pca.py
name change: cos into cosine
change way of calculating cosine_kernel in metrics/pairwise.py
add test for cosine_kernel in metrics/test_pairwise.py
correct indent pb and re-edit cosine_kernel help in metrics/pairwise.py
fix style issue by running pep8 on metrics/pairwise.py and on metrics/tests/test_pairwise.py
remove duplicated test_cosine_kernel() in metrics/tests/test_pairwise.py
change test_cosine_kernel to include normalize from preprocessing.py in metrics/tests/test_pairwise.py
remove duplicated dimension check in metrics/pairwise.py
add reference to cosine similarity in cosine_kernel help from metrics/pairwise.py
modify cosine_kernel func to use normalize from preprocessing.py and change the test_cosine_kernel adding scipy.sparse inputs respectively in metrics/pairwise.py andmetrics/test_pairwise.py
modify test_cosine_kernel to compare result obtain with linear kernel in metrics/tests/test_pairwise.py
FIX: add prefix 'np.' to sqrt for test_cosine_kernel in metrics/tests/test_pairwise.py
FIX: move import of normalize function into the cosine_kernel call in metrics/pairwise.py
Brian Cajes (6):
Improving code coverage for datasets module. Moved dataset imports inside test_data_home, because it is preferable for import errors to only affect the tests that require those imported methods. My first commit to scikit. -bcajes
revert to original import placement style
Improving code coverage for datasets module. Moved dataset imports inside test_data_home, because it is preferable for import errors to only affect the tests that require those imported methods. My first commit to scikit. -bcajes
bring datasets.base to 97% coverage with a few more tests
removing backup file
checking data.shape for each test dataset
Brian Cheung (15):
Discretization method for spectral clustering added along with tolerence setting to loosen eigendecomposition constraints
Documentation and small bugs fixed and code cleaned up
Small comments/constants added
Added more info in documentation
Small aesthetic fixes to discretization
pep8 formatting
More description of the discretization algorithm.
Even more description of the discretization algorithm.
Documentation changes, removed more camel case variables
Fixed some memory inefficiencies and clearned up documentation and code semantics
Example for spectral clustering embedding handling
Added newline to the end of file
removed a hardcoded value
Modified lena segmenation example to include different embedding solvers
Removed savefig
Christian Jauvin (4):
Mechanism to propagate optional estimator.fit arguments when using CV
changed **fit_kwargs to explicit fit_params dict
make sure that param has len attr + a test
replaced assert with assert_true + error msg
Christian Osendorfer (16):
Factor Analysis -- implemented with EM + SVD.
TST: Make factor analysis test repeatable.
Extended faces decomposition example with Factor Analysis.
Factor Analysis learns variance of generative model for every dimension. Illustrated with faces.
pep 257.
Make sure that psi=0 does not break em.
Some documentation for FA.
More or less same code already available.
Plot noise variance for FA. Changed some things to make plot_gallery usable for this, too.
Adding some plots for FA. Ordering of articles must be adopted.
Extended test a bit.
Added score function.
Two iterations are enough for the test.
score works like ppca.score().
adapted to new signature of score().
Moved paragraph on FA before ICA.
Christoph Deil (1):
Fix typo in README
Conrad Lee (8):
metrics.py: modified precision_recall_curve to lower computational complexity
metrics.py: pep8 and other cosmetic changes
metrics.py: Added more comments to precision_recall_curve.
metrics.py: bugfix in precision_recall_curve and added tests
metrics.py: more detailed comment in precision_recall_curve
metrics.py: pep8
metrics.py: COSMIT more commets on precision_recall_curve
metrics.py: COSMIT, replaced cryptic np.r_ with np.hstack
Corey Lynch (10):
cythonized expected_mutual_information
added authors
Changed example svc kernel to be linear, however the error curve ends up flat under the new kernel.
Used more extreme values of C to show a more pronounced error curve.
Took out a save image line
Edited docs to reflect change in kernel used.
added yticks
added yticks
added yticks
limited range of C cross validation
Daniel Nouri (14):
Test qda with 'priors' parameter
Test QDA.covariances_ attribute
Don't cover this deprecated method
Test non-normalized GaussianProcess
Test _BaseHMM._decode_map
Test _BaseHMM.{predict,predict_proba}
Make this bit of code more compact (and improve code coverage).
Remove unused code branch. (_hmmc must be always available nowadays.)
Remove stale test code
Remove obsolete comment
Improve cross_validation test coverage: 94% -> 99%
Improve metrics.metrics code coverage: 95% -> 100%
Improve svm.base test coverage: 92% -> 98%
Add docs for `vocabulary_` and `stop_words_` attributes of Countvectorizer.
Denis Engemann (1):
FIX + ENH: catch custom function argument errors and inform user
Doug Coleman (3):
BUG: Don't test test_k_means_plus_plus_init_2_jobs on Mac OSX >= 10.7 because it's broken. See #636. Closes #1407.
BUG: Fix the random_state on make_blobs() in test_classifiers_classes(). Fixes #1462.
BUG: Make a RandomState object and use it in test_transformers(). Fixes #1368.
Eugene Nizhibitsky (1):
Fix staged_predict_proba() in gradient_boosting.
Fabian Pedregosa (17):
Print running time as a floating-point number with two decimals.
Merge pull request #1138 from fabianp/doc_float
Robustify LARS. Fixes issue #487
New (faster) implementation of isotonic regression
ENH Improve Ridge's conjugate gradient descent
Added the paper I used to implement isotonic_regression.
Add support for preference contraints in svmlight format.
FIX: query_id parameter and other cosmetic changes
Add test for load_svmlight_files
Merge pull request #1182 from fabianp/svmlight
FIX: typo in ValueError message.
Add support for query_id in dump_svmlight_file
DOC: added svmlight qid support to whats_new.rst
Python3 compat: print()
ENH: Consider order in X for IsotonicRegression.
Better tests + cosmetic changes.
Store X as an ordered array.
Gael Varoquaux (131):
DOC: add a reference on multi-output trees
MISC: docstring work
BUG: fix setuptools feature
MISC: small docstring work
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Minor changes to contributing
BUG: parallel computing in MDS
BUG: deprecated k parameter in MiniBatchKMeans
BUG: copy and keep ordering
BUG: remove leftout debug prints
DOC: Enet alpha=0 => advice to use LinearRegression
MISC: add ltsa in docstring
ENH: MCD for large dataset
BUG in error message for k-means
BUG in error msg for spectral clustering
BUG: propagate random-state in MCD
DOC: protect `classes_` for valid rst
FIX: doctests under Windows 64bit
Update changelog
DOC: use nosetests rather than sklearn.test()
ENH: support arbitrary dtype in kNN classifiers
TEST: predict_proba in knn classifier with y string
DOC: fix doc mistakes
DOC: another layout fix
DOC: add doc on making a release
TST: cater for 0.9 not > 0.9
BUG: obey numpy 1.7's stricter rules
Merge remote-tracking branch 'origin/pr/1234'
BUG: cater for dev versions of numpy
MISC: use toarray instead of todense
BUG: RandomizedPCA needs random_state set
ENH: make RandomizedPCA.fit idempotent
TST: fix doctest
TST: fix test counting warnings
BUG: follow scipy API change
DOC: typo
DOC: improve the model selection exercise
ENH/FIX add a lobpcg solver to spectral embedding
MISC: decrease verbosity by default
FIX: numerical stability in spectral
MISC: addressing @satra's comments
ENH: make sure that spectral EVD is solve once
MISC: @agramfort's comments
PEP8
BUG: fix test error
BUG: make precision_recall invariant by scaling probs
BUG: fix setuptools feature
MISC: split example in two plots
API: change 'embed_solve' to 'assign_labels'
TST: increase coverage in spectral clustering
DOC: add docs of assign_label in spectral clustering
COSMIT: long remarks go in 'notes' section
BUG: restore numpy 1.3 compatbibility
MISC: minor clean ups in hmm code
Merge pull request #1290 from tjanez/master
COSMIT: pep8 in arrayfuncs.pyx
BUG: dot on sparse matrices broken in recent numpy
BUG: fix doctest bug
DOC: improve wording in covariance docs
DOC: typo
COSMIT: pep8, wording, layout
DOC: fixed string formatting in example
MISC: remove unused import
BUG: LassoLars path ending contained junk
TEST: one addition test on the length of the path
TEST: test that alpha is decreasing in LassoLars
BUG: lars corner case with path length == 1
ENH: multi-target Lars: lists rather than arrays
ENH: early stopping LARS for degenerate active set
MISC: address comments
MISC: more precise warning
WIP: drop for good correlated regressors
MISC lars_path: cleaner code in degenerate case
ENH: early stopping for lars
TST: add a test for lasso and lars
MISC: comment
ENH lars_path: early stopping after drop for good
TST: difficult test for early stopping
COSMIT: better comments
BUG: missing import introduced by rebase
DOC: Update whats_new with lars improvements
BUG: compat with numpy 1.3
DOC: spelling
BUG: AUC should not assume curve is increasing
COSMIT
DOC: LinearRegression document the shape of coef_
DOC: n_responses -> n_targets
TEST: decrease precision in test_lars_drop_for_good
BUG: imports should be locals
MISC: wording of doc/comments in example
ENH: RandomForestEmbedding in lle_digits example
DOC: cross-ref Random Forest embedding and manifold
DOC: list of dicts in GridSearchCV
DOC: wording and layout on front page
ENH: update joblib to 0.7.0a
BUG: fix properties on joblib files
BUG: Add forgotten file
BUG: update joblib to 0.7.0b
BUG: fix murmurhash compilation with recent Cython
ENH: use broadcasting, not tile
COSMIT: pep8
TEST: fixing randomly failing test
ENH: rng local to tests
TEST: add a test of sample weights
TST: improve last test
BUG: fix sample_weights in ridge
BUG: shape bug in tests
BUG: fix sample weights in ridge
BUG: Ridge: sample_weights in intercept
TST/BUG: test_common sample_weights in ridge
ENH: random reassignements in MiniBatchKMeans
ENH: fine tuning to the random assignement
DOC: example of dict-learning with KMeans
DOC: improve online KMeans example
DOC: dict learning with kmeans in narrative doc
DOC: fix typo
BUG: check n_clusters == len(cluster_centers_)
PEP8
DOC: change the example to lighter dataset
ENH: more control on reassignment in MiniBachKMeans
DOC: link to example
DOC: add comment
DOC: complete whats_new
TST: random reassignment in MiniBatchKmeans
TST: test verbosity mini_bach_kmeans
ENH: control random_state in MiniBatchKMeans
COSMIT: simplify parallel code in multiclass
DOC: put math at back, simplify formulation
MISC: fix rst in whats_new
MISC: index arrays with integers
DOC: voronoi + kmeans picture
Gilles Louppe (54):
FIX: bug in multi-output forest.predict_proba
Check for memory errors (1)
Check for memory errors (2)
Check for memory errors (3)
Avoid useless if-statements
Added a comment to clarify initial capacity
Merge pull request #1144 from glouppe/tree-malloc
DOC: return values of make_moons and make_circles
Merge pull request #1197 from glouppe/master
FIX: prevent early stopping in tree construction
FIX: prevent early stopping in tree construction (2) + Test
Merge pull request #1263 from glouppe/fix-1254
Merge pull request #1269 from mrjbq7/doc-fixes
ENH: Simplify the shape of (n_)classes_ for single output trees
ENH: Simplify the shape of (n_)classes in forest
PEP8
TEST: regression test for shape of (n_)classes
TEST: enforce flat classes_
What's new: API changes
ENH: better names for variables
What's new: added :class: keyword
FIX: convert predictions into a numpy array
FIX: docstring tests
Merge pull request #1445 from glouppe/tree-shape
What's new: typo
Merge pull request #1388 from arjoly/issue1047_gradient_boosting_uses_decision_trees
Merge pull request #1458 from seberg/contig_strides
What's new: fix by @seberg
Checkout files from ndawe:treeweights
FIX: roll back some changes
FIX: what's new
flake8
ENH: early binding + allocate features at tree creation (by @pprett)
FIX: oob test
DOC: sample_weight=None
DOC: what's new
DOC: typo
DOC: cosmit
FIX: use sklearn.utils.fixes.bincount
ENH: use random_state.shuffle
ENH: import aliases
ENH: import aliases (2)
ENH: import aliases (3)
PEP8 (some)
TEST: sample_weight
TEST: sample_weight (once more)
FIX: iris.target
FIX: raise an exception if negative number of samples
TEST: use rng
FIX: do not overwrite min_samples_split
FIX: set min_samples_split=2 by default
DOC: updated docstring
Typo
FIX: what's new
Immanuel Bayer (9):
add dual_gap_ and eps_ to Enet and Lasso docstring
extend eps_ description
renaming 'learn_rate' in 'learning_rate'
ENH hompage add links to headers in left panel
ENH add link to Citing
ENH renaming 'max_iters' to 'max_iter' for consistency
DOC missing class mention
ENH renaming 'n_atoms' to 'n_components' for consistency
ENH fix pep8
Jacques Kvam (4):
add verbose output for gradient boosting algorithms
Changed verbose to int, added a low verbose option to just print '.'.
remove '\r' and format numbers to be fixed width, 7 digits of precision
fix GradientBoostingClassifier by passing verbose as a keyword argument
Jake VanderPlas (6):
Merge branch 'cov-speedup' of git://github.com/vene/scikit-learn into vene-cov-speedup
speed up symmetric_pinv
additional speedup: all eigenvalues are real for symmetric matrix
@jakevdp's version of pinvh
DOC: add google analytics theme option
clarify documentation for radius_neighbors
James Bergstra (8):
ENH: adding iter_limit to libsvm
FIX: committing updated Cython-generated libsvm bindings
ENH: Solver iter_limit emits warning instead of raising exception
ENH: renaming iter_limit -> max_iter
FIX: missing file hidden among the Cython output
ENH: hint about data normalization when SVC stops early
FIX: adding missing c files from cython
ENH: assert -> assert_equals
Jaques Grobler (41):
changed includes back - change broke JENKINS build
not the problem afterall - switch back
add first collapsible toctree test
moved buttons to themes
working version
Links now clickable
-collapse toc moved to front page-
button colour change + comments
fixes - seemingly good version
highlighting of + implemented
-line highlight bug fixed, buttons changed, full expansion added
small bug fix and colour tweak
nitpick fix
cleanups
cleanups
toggle bug fixed
highlight fix
what`s new updated
remove `steps` from Attributes of docstring
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Merge pull request #1331 from jaquesgrobler/master
Merge pull request #1367 from fannix/master
Merge pull request #1369 from AlexandreAbraham/fix_doc_clean
doc fix - trailing underscore and init param update
goodness of fit fix
trailing whitespace sentence
Merge pull request #1372 from jaquesgrobler/doc-fix-dev_guide
plot fix
variable name change
new example added for manifold learning
Andy`s suggestions
links for MDS
small changes
final changes
pep8
heading change
added links to astropy and scipy workflow guids
Merge pull request #1564 from jaquesgrobler/contributor_guide_links
remove 1000`s of warnings from example
Merge pull request #1592 from jaquesgrobler/master
Add temporary survey banner
John Benediktsson (2):
DOC: fix 'Controls' typo in sklearn.ensemble.forest.
COSMIT: fix typo in AUTHORS.rst.
Kenneth C. Arnold (1):
Mark Cython outputs as binary so their changes don't clutter diffs.
Kyle Beauchamp (10):
Added code to address issue #1403
In preprocessing.binarize, eliminate zeros from sparse matrices
Added feature for issue #1527
Minor PEP8 fixes for issue #1527
Minor docstring fix for issue #1527
Added tests and docs for normalized zero_one loss
Fixed pep8 spacing issue and floating point doctest issue
Added CSC matrix testing for binarize and added type tests.
Added MinMaxScaler inverse_transform for issue #1552
Dummy commit to trigger travis
Lars Buitinck (108):
DOC copyediting
TST (near-)empty lines and explicit zeros in SVMlight loader
COSMIT use property.setter in sklearn.svm
ENH performance of TfidfTransformer
COSMIT replace useless safe_sparse_dot in chi2 with np.dot
BUG fix broken top-10 features printing in text clf example
DOC copyedit HMM documentation
COSMIT const and void* correctness in liblinear wrapper
ENH refactor liblinear prediction code and add classes_ member
COSMIT liblinear C code cleanup
COSMIT comment out more unneeded liblinear code
DOC + COSMIT LogisticRegression: docstring + rewrite predict_proba
Merge pull request #1141 from pprett/sgd-predict-proba
DOC small fixes to SGD docstrings
COSMIT rm svm.sparse tests to prevent deprecation warnings
ENH micro-optimizations in SVMlight loader
BUG rm RidgeClassifier from 20newsgroups
Merge pull request #1143 from larsmans/refactor-liblinear
ENH no more distinction between "sparse" and "dense" LinearSVC
COSMIT rm deprecated SGDClassifier.classes property
COSMIT clarify L1/L2 LR sparsity demo
DOC fix link for IsotonicRegression
DOC fix IsotonicRegression docstrings
BUG allow array-like y in RFE
DOC RFE docstring + link RFECV in narrative docs
BUG rm LARS from linear_model.__init__
COSMIT refactor linear classifiers
TST improve Ridge test
COSMIT use LinearClassifierMixin in RidgeClassifier
COSMIT + DOC univariate feature selection
COSMIT re-indent docstring for safe_mask
BUG make GridSearchCV work with non-CSR sparse matrix
COSMIT rm deprecated class_weight from fit in Ridge
Revert "BUG rm RidgeClassifier from 20newsgroups"
ENH add max_iter argument to Ridge estimators
DOC Ridge improvements in whats_new
Merge pull request #1169 from larsmans/ridge-cg
COSMIT rm deprecated stuff -- lots of it
DOC rm references to deprecated stuff
TST writable coef_ and intercept_ on LogisticRegression
ENH let DictVectorizer build a CSR matrix directly and use array.array
DOC DictVectorizer returning CSR in ChangeLog
Merge pull request #1193 from larsmans/dictvectorizer-csr
COSMIT error messages in GenericUnivariateSelect
ENH perform feature selection on scores, not p-values, when possible
DOC some improvements to FeatureUnion docs
DOC LaTeX error in SVM narrative docs
ENH better error messages in CountVectorizer for empty vocabulary
TST CountVectorizer with empty vocabulary
Merge pull request #1208 from larsmans/check-empty-vocabulary
Merge pull request #1211 from kcarnold/gitattributes
DOC typos in README
DOC feature selection by scores instead of p-values
DOC various typos and other minor stuff
DOC clarify zero_based's implications in SVMlight loader
Merge pull request #1204 from larsmans/mi-feature-selection
BUG + DOC l1_ratio in SGD and CD
COSMIT correct error msgs in SGD and make them more consistent
Merge branch 'pr/1214'
DOC let BibTeX handle its own capitalization, except for {P}ython
BUG NaN handling in SelectPercentile and SelectKBest
COSMIT rm unused import
COSMIT website address + copyedit in __init__.py
DOC move implementation details on mixins to comments
Revert (rebased) merge of euclidean_distances speedup
ENH allow more than 1000 linear SVMs with custom random seeds
BUG halve the number of LinearSVCs
COSMIT use np.clip in SGD
ENH fit_transform on KMeans
ENH input validation in chi2, error for negative input
Merge branch 'master' into pr/1279
ENH OneHotEncoder docs + TypeError + test active_features_
ENH cut down on memory use of text vectorizers
DOC copyedit tutorials
COSMIT rm outdated file of changes to liblinear
Merge pull request #1335 from robertlayton/clustdocs
DOC typo in k-means docs
Merge pull request #1366 from agramfort/move_isotonic
DOC grammar in isotonic regression narrative docs
ENH feature hashing transformer
DOC narrative documentation for feature hashing
ENH speed up hashing and reduce memory usage by 1/3
ENH allow (feature, value) pairs in FeatureHasher
ENH 20newsgroups example for FeatureHasher
ENH + DOC FeatureHasher
ENH add dict support to FeatureHasher and make it the default input_type
Merge pull request #1374 from jakevdp/doc_GA_flag
BUG enforce and document max. n_features for FeatureHasher
DOC update Ubuntu installation instructions
FIX smoothing in Naive Bayes and refactor the discrete estimators
COSMIT no diff for pairwise_fast.c
DOC credit @sjackman in what's new for BernoulliNB fix
COSMIT refactor input validation code; skip some issparse calls
BUG Cholesky delete routines wouldn't compile on Solaris
COSMIT simplify unique_labels in sklearn.metrics
COSMIT shut up the build by calling np.import_array in Cython modules
Merge pull request #1556 from larsmans/cython-cleanup
COSMIT wrong path in .gitattributes
Update sklearn/metrics/metrics.py
update year in copyright notices
BUG don't write comments in SVMlight dumper by default
BUG hotfix for issue #1501: sort indices in SVMlight i/o
DOC fix travis URLs in README
TST sorting CSR matrix indices in SVMlight file handling
DOC improve cosine similarity docs
COSMIT make BaseVectorizer a mixin
DOC copyedit HashingVectorizer docs
Merge pull request #1598 from amueller/naive_bayes_class_prior_rename_revert
Luis Pedro Coelho (1):
cd_fast: use square norm directly
Mark Veronda (2):
Type-os and added great links to learning more about Machine Learning
Feedback from @amueller
Mathieu Blondel (117):
Use fixed random state in isotonic regression example.
Note on the use of X in isotonic regression.
Fix confusing notation in isotonic regression.
Fix latex formula in isotonic regression doc.
Release manager change + fix Satra's URL.
Move solver option to constructor.
Add lsqr solver.
BUG: transmit parameters correctly from Ridge to ridge_regression.
Can afford better precision in news20 example.
Fix docstrings and doctests.
Add minimalistic test for each solver.
Fix damp parameter.
Fall back to dense_cholesky if sample_weight is given.
lsqr is not available in old scipy versions...
Better documentation on the choice of solver.
PEP8!
Cosmit: not a fan of defining a function in a loop :)
Update what's new.
More accurate API change description.
Fix warning message.
Merge pull request #1215 from amueller/pipeline_muliclass
Merge pull request #1237 from kalaidin/typos
Merge exthmath tests into the same file.
Add common assertions to sklearn.utils.testing.
Fix density utility when input is sparse.
Typo.
Fix test failure.
Use sklearn.utils.testing in tests.
Merge branch 'master' of github.com:scikit-learn/scikit-learn
More use sklearn.utils.testing.
Even more sklearn.utils.testing.
Missing random_state in LinearSVC.
Merge pull request #1323 from dnouri/countvectorizer_doc_1154
FIX: vocabulary_ maps to feature indices.
Merge pull request #1320 from dnouri/test_coverage
Merge branch 'sgd_learners' of https://github.com/zaxtax/scikit-learn into passive_aggressive
Rename pa.py to passive_aggressive.py.
Cosmit: random_state is not necessary.
Fix many bugs and test PA-I.
Do not expose C in SGDClassifier / Regressor.
Implement and test PA-II.
Add SquaredHingeLoss.
Test different losses.
Add squared epsilon insensitive loss.
Test PA-II (regression).
Fix random_state in SGD.
Update narrative documentation.
Fix example.
Credit myself.
Fix see also.
Fix a few test failures.
Add one more test for PassiveAggressiveRegressor.
Fix underflow detected by test_common :)
Update document classification example.
Fix doctests.
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Better documentation for C.
Add PassiveAggressive* to class reference.
Remove sample_weight and class_weight from PassiveAggressive*.
Add tests for partial fit.
Document epsilon.
Better documentation for epsilon in SGD.
Remove predict_proba from Perceptron and PassiveAggressiveClassifier.
Remove transform from PassiveAggressive*.
Fix typos and wording in RandomForestEmbedding.
Indicate dimensionality in RandomForestEmbedding example.
Cosmit: use less memory in feature hasher tests.
Cosmit: make KernelCenterer a private attribute in KernelPCA.
Improve KernelCenterer docstring.
Add add_dummy_feature.
Add RandomClassifier and tests.
Fix tests.
Add docstrings for RandomClassifier.
PEP8.
random_state=None by default.
Remove label encoder.
Implement predict_proba.
Add some narrative doc.
Address @amueller's comments.
Rename to dummy.DummyClassifier.
Add DummyRegressor.
Add dummy estimators to references.
Add what's new entry.
Add comments.
Check returned types.
Test expectations.
Test string labels.
Test exceptions.
Cosmit: save one line.
Address @amueller doc comments.
Skip common tests for Dummy*.
Typo :/
Add example in docstring.
Add to references.
Merge pull request #1382 from mblondel/add_intercept
Merge pull request #1373 from mblondel/random_clf
Remove unused import.
Improve error message when vocabulary is empty.
Fix bug in sqnorm (used by PassiveAggressive).
Link to travis.
Specify branch in status button.
Add missing assertion.
Update what's new.
Cosmits and typos.
Add perceptron loss to plot.
threshold parameter was ignored in SquaredHinge loss.
Welcome to Wei Li and Arnaud Joly.
Clean up test_pairwise.py.
More clean up of test_pairwise.py.
Cosmit: break up long line.
Merge pull request #1530 from agramfort/doc_lasso
X is not a constructor parameter.
Add missing types to docstring.
Move more minor contributors to what's new file.
Remove contact address.
Merge pull request #1561 from kyleabeauchamp/MinMaxScaler_Inverse
Merge pull request #1536 from kyleabeauchamp/issue-1403
Matti Lyra (2):
Fixed an issue where CountVectorizer.decode leaves file pointers open after reading the contents of the file. This produces unpredictable behaviour as closing the file pointer is left to the implementation of the python interpreter.
Changed the CountVectorizer charset default back to 'utf-8' instead of 'utf8'. This was due to debugging on my local machine.
Michael Eickenberg (6):
Added strided patch extractor to feature_extraction/image. Extracts patches 16x faster on the MiniBatchDictionaryLearning example
Now added extract_patches for random extraction as well
Now replaced max_patches part by fancy indexing
removed stuff i commented out
testing for correct output shapes and patch content of the last patch for 1 to 3 dimensional arrays
Changes in documentation and notation
Mikhail Korobov (2):
P3K fix incorrect import
P3K: division should produce integer.
Miroslav Batchkarov (1):
fixed the __repr__ method of cross_validation.Bootstrap, which failed if self.random_state is None
Nelle Varoquaux (17):
ENH: Isotonic regression
MDS is now using the new isotonic_regression submodule
Added tests to isotonic_regression
DOC - added paragraph in user documentation on the isotonic regression + an example plot.
More documentation
FIX IsotonicRegression only takes vector input, hence don't test it in the common estimators
ENH IsotonicRegression now uses variable names that have more than 3 letters
ENH better error messages on the IsotonicRegression
Added a predict method to the IsotonicRegression
FIX random_state in MDS was not initialized properly
ENH isotonic regression is now slighty more robust to noise
Added test to check whether the isotonic regression changed y when all ranks were equal
ENH uses the IsotonicRegression classifier instead of the method
FIX the mds example did not plot the NMDS
FIX - nmds now uses the same scaling as previously
ENH we require a version of sphinx sufficient for "new" numpy_ext to work
FIX instead of appending numpy_doc to the list of extensions, directly add when creating the list
Noel Dawe (6):
ignore splits that yield nodes with net negative weight in find_best_split
rm unneeded negative weight logic in Criterion.init_value and Gini.eval
add note about negative weight treatment in BaseDecisionTree.fit
add negative weights test (currently fails): predict_proba should still be valid probabilities
FIX: negative weight test. do not allow any class to have negative weight after a split
DOC: document negative weight treatment in the case of classification
Olivier Grisel (101):
ENH: pass verbose consistently in forest module
cosmit
FIX: wrong probabilities for OvR LogisticRegression
ENH: make test_common check normalized probabilities
Merge pull request #1189 from fabianp/svmlight
Merge pull request #1187 from ogrisel/bugfix-logistic-ovr-probabilities
FIX: broken doctest for DictVectorizer
FIX: missing figures in FA narrative doc
Merge pull request #1266 from cdeil/patch-1
Merge pull request #1292 from aymas/pass_rng_kmeans_gmm
Merge pull request #1344 from mattilyra/CountVectorizer.decode
FIX: missing # for comment in pyx file and readded missing AMI docstring
FIX: lars drop for good platform specific test failure
FIX #1354: machine precision assertion failure in test_liblinear_random_state
Merge branch 'master' of github.com:scikit-learn/scikit-learn
Merge pull request #1361 from astaric/py3k
DOC: make MinMaxScaler example snippet readable outside of other sections context
DOC: more improvements / fixes on the MinMaxScaler doc
Merge pull request #909 from larsmans/hashing-trick
Merge pull request #1397 from SnippyHolloW/travis
Improved bench_covtype.py to load data faster and support configurable n_jobs
Merge pull request #1415 from SnippyHolloW/travis
Merge pull request #1418 from kuantkid/archlinux
Merge pull request #1408 from satra/fix/rebase1396
Merge pull request #1425 from arjoly/enh_bench_covertype
Merge pull request #1424 from jaquesgrobler/plot_omg_fix
FIX #1417: move nosetests configuration parameter to setup.cfg
Remove doctest-options from setup.cfg as not supported in old version of nose
Merge pull request #1430 from erg/issue-1407
Merge pull request #1429 from tnunes/fix_pipeline_fit_transform
Merge pull request #1440 from amueller/matplotlib_requirement
Display the test names to understand which test is triggering the segfault on jenkins
FIX: fixed random_state for heisen doctest failure in multiclass module
Merge pull request #1468 from erg/random-failures-12345
Delete iris.dot in tree.rst doctest
FIX: seed blobs dataset to have a stable spectral clustering under OSX 10.8
Merge pull request #1470 from kuantkid/fix_spectral_cluster_test
Add comment in test_spectral_clustering_sparse
Merge pull request #1465 from AWinterman/issue-1017
first pass at implementing sparse random projections
DOC: better docstrings
DOC: more docstring improvements
Remove non-ASCII char from docstring
use random projections in the digits manifold example
test embedding quality and bad inputs (100% line coverage)
typos
one more typo
OPTIM: CPU and memory optim by using a binomial and reservoir sampling instead of direct uniform sampling in the n_features space
note for later possible optims
fix borked doctests
make it possible to use random projection on the 20 newsgroups classification example
FIX: raise ValueError when n_components is too large
remove the random projection option from the 20 newsgroups example
leave self.density to 'auto' to implement the curified estimator pattern
more curified estimator API
useless import
change API to enforce dense_output representation by default
ENH: vectorize the johnson_lindenstrauss_bound function
started work on plotting the JL bounds to be used in the narrative documentation
More vectorization of the johnson_lindenstraus_bound function
More work on the JL example to plot the distribution of the distortion
WIP: tweaking JL function names
check JL bound domain
JL Example improvements
WIP: starting implementation implicit random matrix dot product
working on implicit random projections using a hashing function
OPTIM: call murmurhash once + update test & example
first stab at CSR input for hashing dot projections
implemented dense_output=False for hashing_dot
refactored test to check that both materialized and implicit RP behave the same
fixed broken seeding of the hashing_dot function
leave dense_output=False by default
use the 20 newsgroups as example dataset instead
make it possible to use a preallocated output array for hashing_dot
missing docstring and s/hashing_dot/random_dot/g
eps=1.0 is no longer a valid value
Typo / fix in JL lemma example
FIX: MinMaxScaler on zero variance features
Simpler inline comment
Add one more test for MinMaxScaler on newly transformed data
ENH: issue warning when minmax scaling integer data + test
ENH: add the squared hinge loss to the SGD loss example
Merge pull request #1517 from amueller/lda_qda_cleanup
Merge pull request #1562 from kmike/master
P3K: avoid iteritems / itervalues when feasible
P3K: decode error message in svm wrapper
ENH: output processing speed in MB/s for vectorizer example
Initial work on hashing vectorizer
Add fit_transform support using the TransformerMixin + missing ABCMeta marker
Improved the clustering example with HashingVectorizer
Remove TransformerMixin from vectorizers and do a direct fit_transform alias for HashingVectorizer instead
Improve module docstring of document clustering example
cosmit
Updated whats_new.rst
DOC: Started section on hashing vectorizer in narrative section
DOC: narrative doc for HashingVectorizer
DOC: typos
DOC: merged the whats new entries and add links to the narrative doc
DOC: address @mblondel's comments
ENH: measure feature extraction speed in document classification example
DOC: typos
Pavel (1):
Fixed typos.
Peter Prettenhofer (137):
added failing test for clone
rm instance variables learing_rate_type, loss_function, and penalty_type; create them before plain_fit
move get_loss_function to _partial_fit
add test for proper loss instantiation
n_iter must not be 0
refactored input validation; special loss function factory for huber and epsilon insensitive loss
use DEFAULT_EPSILON consistently
rename get_loss_function to _get_loss_function
Merge remote-tracking branch 'upstream/master' into sgd-clone-fix
added test to expose the predict_proba w/ sparse matrix regression
fix the predict_proba w/ sparse matrix regression by using shape instead of len
cosmit
followed @larsmans tip to get rid of _decision_function
fix docstring of predict_proba
add predict_log_proba and test; better docstrings
wip on fx interactions for GBRT
Merge branch 'master' into gbrt-interactions
implemented partial dependecy plot
fix: grid and model
cleaned tree traversal and sorted out weighting
cythonized and cosmit
automatically create grid from training data
add cartesian product
partial dependency plot example from ESLII 10.14.1
Merge branch 'master' into pr/975
docstrings for init and loss_
cosmit
added Emanuele to authors
Merge remote-tracking branch 'upstream/master' into pr/975
Merge branch 'master' into gbrt-interactions
Merge branch 'master' into gbrt-interactions
Merge branch 'master' into gbrt-interactions
add learn rate to partial dependency function
common ylim; comment out 3d plot
make fit_stage private
return axes instead of grid
3d plot of 2-way interaction plot
Merge branch 'master' into gbrt-interactions
multi-class is supported
cosmit
doc: use n_iter instead of epochs; remove backslash
Merge branch 'master' into gbrt-interactions
california housing dataset
cosmit
use California housing dataset loader
Merge branch 'master' into gbrt-interactions
remove legacy code
Merge remote-tracking branch 'upstream/master' into gbrt-interactions
renamed dependency -> dependence; docstring and cosmit
typo
fix: feature_importances_
rename dependency -> dependence
rename dependency -> dependence
add partial dependence plot example
document sample_mask and X_argsorted in BaseDecisionTree.fit and validate inputs using np.asarray (added two tests as well)
Merge branch 'master' into gbrt-interactions
tidy up deprecated warnings for learn_rate
Merge branch 'master' into gbrt-interactions
raise error if both grid and X are specified
initialize estimators_ with empty array not None
more input validation for partial dependence and doctest
tests for partial_dependence
rename learn_rate -> learning_rate
input validation for grid
test cases for grid
pep8
added test for cartesian
add partial dependence to whats new
documentation for partial dependence plots
add module imports
typo
cosmit
call pl.show
renamed datasets.cal_housing to datasets.california_housing
add plot titles
cosmit
Merge branch 'master' into gbrt-interactions
cosmit: docstrings
better narrative docs for partial dependence
cosmit: footnote header
empty instead of zeros
Merge branch 'master' into gbrt-interactions
more explicit typing (int32, float64)
Merge branch 'master' into gbrt-interactions
Merge branch 'master' into gbrt-interactions
add plotting convenience function
uses plotting convenience function
moved partial dependence into its own module.
doctest fix + cosmit
fix imports
remove partial dependence (moved to own module)
updated example
fix imports (partial dependence)
fix: california_housing not cal_housing
cosmit
switch axis for 2-way plot; better to compare with above plot
added partial dependence and fetch_california_housing to classes
better documentation
fix links
add partial dependence module
add test for staged_predict_proba
Merge branch 'master' into pr/1409
Merge branch 'master' into gbrt-interactions
better formatting of xticks (prevent overlap)
show how to use ``partial_dependence`` to generate custom plots.
doctest skip for plot function
fix doctests skip
renamed: ncols -> n_cols;
test decorator to skip tests if matplotlib cannot be imported
smoke test for plot_partial_dependence
fix: doc rename partial_dependence_plots -> plot_partial_dependence
Merge remote-tracking branch 'upstream/master' into gbrt-interactions
better input checking (e.g. for str features)
better handling of multi-class case (w/ symbol labels)
code snippets for narative doc and restructuring
fix: random_state got initialized in fit_stage; caused same feature subsample in each tree
add test for gbrt random_state regression
Merge branch 'master' into gbrt-random-state-fix
Merge branch 'master' into gbrt-interactions
doctest skip: matplotlib not available on travis
fix: doctest in ensemble.rst
Merge branch 'master' into gbrt-interactions
rephrased the one-way PDP description
Merge branch 'master' into gbrt-interactions
topics -> topic
Merge remote-tracking branch 'upstream/master'
use Agg backend with warn=False for matplotlib enabled tests
check in ``if_matplotlib`` if $DISPLAY set
use subplots_adjust instead of tight_layout
use 100 instead of 800 n_estimators; looks the same but faster; ESLII uses 800
ZipFile context manager is only available in Python >= 2.7
cosmit: remove fourth quote
set min_density when growing deep trees during gradient boosting
sampling w/ replacement via sample_weights
fix: docstring for power_t in SGDClassifier was not correct (0.25 instead of 0.5)
cosmit: rephrased doc
zero_one_loss now does normalize on default.
Richard T. Guy (4):
Switched dynamic default args in random forest
Added test
Switched default parameter to tuple from lists.
move tuple back into arguments
Rob Zinkov (30):
Adding guide on how to contribute to project
Fix indentation
Removed tabs from indentation
COSMIT: noting that PRs don't send mail to mailing list
Moved link for further info to be more prominent
Adding Passive Aggressive learning rates
Added documentation to stochastic_gradient
Added to documentation
Added documentation and removed PA
Added tests
COSMIT: spelling correction
Adding example
Added smoothing to example
COSMIT typo
PEP8 fix
PEP8 COSMIT
PEP8 COSMIT
Enforcing non-negative step-size
Split out PassiveAggressive Classifier into its own object
Adding PassiveAggressiveRegressor estimator
COSMIT
Added documentation for new classifier and changed seed to random_state
Fixed typo
Renamed learning_rate loss in PassiveAggressive
Correct documentation
Corrected doctests
Fix indentation
Fixed docstrings and seed tests
Fresh fixes of grammar errors
Grammar fixes
Robert Layton (8):
Update to the clustering.rst module file for k-means. Added a plain language description and the objective function.
Updated fixes from larsmans
Merge pull request #1478 from amueller/pep8
Merge pull request #1451 from amueller/chunksize_batchsize_rename
First draft of new Affinity Propogation description in docs.
Who doesn't love equations?
Spelling
Update doc/modules/clustering.rst
Satrajit Ghosh (12):
doc: added reference to lobpcg and note about small number of nodes
fix: addressing gael's comments
fix: set syntax
fix: increase robustness of label binarizer test
sty: white space
fix: change affinity check
doc: clean up style and grammar
ref: change name to indicate semantics
fix: removed unused keyword precomputed and clean up if clauses
fix: moved random state check to fit
doc: removed merge diff markers
doc: align hyphens
Scott Dickerson (3):
train_test_split: test_size default is None
Modified docstrings
Modified docstrings and tests
Sebastian Berg (1):
FIX: Do not rely on strides for contiguous arrays
Shaun Jackman (1):
BernoulliNB: Fix the denominator of P(feature)
Shiqiao Du (5):
fixed bug of initialization in hmm.py
added test_fit_with_init to tests/test_hmm.py
pep8, ignored E126-E128
- avoid startprob, transmat, emissionprob containing a zero element by
- check input format of MultinomialHMM.fit
Subhodeep Moitra (1):
P3K: Fixed print related Python3 errors
Tadej Janež (7):
DOC: further improvements to the model selection exercise
DOC: further improvements to the model selection exercise
Merge remote-tracking branch 'upstream/master'
DOC: another improvement to the model selection exercise
DOC: Improved the code that shows how to export a decision tree to Graphviz and generate a PDF file.
Skip doctest for the Python code involving pydot.
Skip doctest for the remaining line involving pydot.
Tiago Nunes (6):
Add fit_transform to FeatureUnion
Change / to (…) line continuation
Add test case for FeatureUnion.fit_transform
Fallback to fit followed by transform if fit_transform is unavailable
Add test case for fit_transform fallback
Fix pipeline fails if final estimator doesn't implement fit_transform
Virgile Fritsch (13):
Merge branch 'cov-speedup' of https://github.com/vene/scikit-learn into cov-speedup
Add comments on optimized precision computations.
Add comments on optimized precision computations.
Merge pull request #1015 from vene/cov-speedup
BF: Address issue #1059 in GMM by adding a supplementary check.
BF: Fix broken tests: change a check for compatibility with HMM.
BF: fix issue #1127 about MinCovDet breaking with X.shape = (3, 1)
Improve doc and error msg in MinCovDet in response to issue #1153.
BF: GridSearchCV + unsupervised covariance shrinkage selection.
Change legend + complete docstrings.
Improve example narrative doc (rewritten intro).
Fix typos in doc.
Add y=None to covariance estimators for API consistence purpose.
Vlad Niculae (65):
We already have the inverse at that step
Replase pinv calls with dgetri
More lapack inverting
Refactored fast_pinv without lapack calls
Compute pseudoinverse using eigendecomposition
Vectorize singular value inversion
Remove unused import
Merge branch 'master' into cov-speedup
Merge remote-tracking branch 'VirgileFritsch/cov-speedup' into cov-speedup
Merge remote-tracking branch 'jakevdp/vene-cov-speedup' into cov-speedup
Update and rename pinvh (by @jakevdp)
Cloned @jakevdp's pinvh tests
Remove odd-looking period in tests
Use pinvh in plot_sparse_recovery example
grammar
Use pinvh in bayes.py
Use pinvh in GMM and DPGMM
We already have the inverse at that step
Compute pseudoinverse using eigendecomposition
Vectorize singular value inversion
Cloned @jakevdp's pinvh tests
Use pinvh wherever it helps in the codebase.
First go at speeding up Euclidean distances
Make it less yellow
More reusable code, speed up symmetric case
Better cython style.
Add dense sparse support and precomputation
FIX: buggy case when X=dense, Y=sparse
Consistent argument naming and useful maintenance notes
FIX using out with sparse matrices
Relative imports, fix todense bug
safe_sparse_dot into preallocated output
Add test for dense_output, fix bug, cleaned up logic
Avoid reallocation in manifold.mds
add type prefix to blas funcs
DOC Clarify the docstrings
Added Cython-generated euclidean_fast.c
Separate dense_output and out parameters, document better
API change: mutually exclusive preallocation and precomputation
FIX: csr_matrix induced unwanted copying
Rename euclidean_fast to _euclidean_fast
Clean setup.py in metrics
ENH: improve test coverage
Add failing test and no-op flip
Sign flipping as suggested by @ogrisel, not in place
Make sign flip in place
Test more seeds for svd sign flipping
Add sign flip as flag in randomized_svd
Make sure svd_flip test actually tests something
Make randomized_svd flipped by default
svd_flip test fails on Travis. Change random seed, see if it helps
Cannot easily ensure non-uniqueness without the fix, just test uniqueness
TEST flipped svd remains correct
FIX: makes our libsvm port compile under MSVC
Merge branch 'master' of github.com:scikit-learn/scikit-learn
DOC: fix typo and formatting around MurmurHash3
DOC: Fixed wrong link and formatting in decomposition docs
DOC: fixed latex and formatting in SVM docs
DOC: more consistency in metrics docstrings
DOC: More consistency in metrics and clustering metrics docstrings
DOC: more consistency in docstrings for unsup clustering metrics & missing link
DOC: fixed missed details in metrics docstrings
DOC: addressed more inconsistencies in metrics docstrings
ENH: use lgamma function from John D. Cook
Merge branch 'master' into lgamma_port
Wei Li (107):
ENH: using coo matrix construction to accelerate calculation of the contingency matrix
FIX: numerial issues in NMI
COMIT pep8
ENH add refs to issue #884
FIX: ADD test cases for exact 0 case, and nmi equal to v_measure case
FIX: accelerate v_measure calculation based on mutual information
COSMIT add doc to clearify how nmi is normalized and pep8 fix
COSMIT pep8 fix for test_supervised
FIX: fixes error caused by break line
Using coo_matrix to accelerate confusion_matrix calculation
COSMIT
ENH add test for testing v_measure is a variant of nmi
COSMIT typos in doc strings
FIX let test use random_state(seed)
PEP8..
FIX typos and vague comments
DOC add comments for log(a) - log(b) precision
COSMIT fails to see the function name use mi rather than mutual information
FIX doctest to check up to 6 digits precision
FIX: eliminate \ for continuation from doctests
FIX issue #1239 when confusion matrix y_true/y_labels has unexpected labels
PEP8
ENH docstring misleading
ADD install guide for archlinux
ADD spectra_embedding for wrap function spectra_embeeding as an estimator from spectral clustering
ENH finish sketch for the estimator wrapper
ENH add warning for inverse transform
ADD test cases for spectra_embedding
ADD empty test scripts
COSMIT
FIX typos
FIX inconsistent typos
FIX nearest_neighbor graph build
ADD add test_examples for pipelined spectral clustering and callable affinity
FIX remote does not have test file wired...
MOV move spectra_embedding from decomposition to manifold
ENH docs partially updated, happy mooncake festival
ENH move spectral_embedding as standalone, fixes for tests
COSMIT
ADD add the laplacian eigenmap to examples
ADD test cases for two components, unknown eigenvectors, unknown affinity
COSMIT
ENH test-coverage
PEP8 test files
ADD spectra_embedding for wrap function spectra_embeeding as an estimator from spectral clustering
rebase: fixing conflict
ENH add warning for inverse transform
ADD test cases for spectra_embedding
ADD empty test scripts
COSMIT
FIX typos
FIX inconsistent typos
FIX nearest_neighbor graph build
ADD add test_examples for pipelined spectral clustering and callable affinity
FIX remote does not have test file wired...
rebase: fixing conflict
ENH docs partially updated, happy mooncake festival
ENH move spectral_embedding as standalone, fixes for tests
COSMIT
ADD add the laplacian eigenmap to examples
ADD test cases for two components, unknown eigenvectors, unknown affinity
COSMIT
ENH test-coverage
PEP8 test files
SYNC doc built error on one machine, sync with another
DOC docs for spectral embedding
DOC dox fix and misc post-rebase things
MRG merge with @Gael's PR 1221 and some name changes
FIX lobpcg, amg drops the constant eigen vectors by default
ADD check for symmetric and check for connectivity
ADD add test for check_connectivity
COSMIT
Change sparse graph to use cs_graph funcs. minor doc changes
Minor doc changes
FIX spectral embedding offers choice whether to drop the first eigenvector
COSMIT
RENAME parameter rename in examples
RENAME rename eigen_tol and eigen_solver, and warning about using old variable name eig_tol and mode
ADD add a test for discretize function
COSMIT and Typo
FIX backwards support
FIX doc fix and test fix
COSMIT
ADD added examples, and eliminate unnecessary imports
FIX nn-affinity does not support sparse input
COSMIT and minor fixes
DOC update whatsnew
FIX: amg requires sparse matrices input
missing _set_diag
fix spectral related testing errors
COSMIT and unused lines
FIX further improve the thresholds
FIX discretization test have shape problem, use coo_matrix instead of LabelBinarizer
Addressing @ogrisel's comments
FIX roc_curve failed when one class is available
COSMIT
DOC fix
TYPO fixes
DOC address @amueller's comment
FIX typo
Update whatsnew
FIX spectral_embedding test erros, ADD spectral embedding to sphere examples
MOD use safe_asarray instead of np.asarray
MISC update my mailmap
MOD address @mblondel's comments
MOD move generating matrix out of the loop
Merge pull request #1563 from kuantkid/sparse_knn_graph
X006 (1):
Updates for DBSCAN clsutering docs
Xinfan Meng (2):
Fix broken links
DOC Change URLs of NNDSVD papers to avoid paywall
Yaroslav Halchenko (6):
Merge tag '0.13' into releases
Merge branch 'releases' into dfsg
Merge branch 'dfsg' into debian
changelog + refreshing patchset
debian/rules - removing exclusion of tests previously failed
added patch changeset_567460a602b4e2fc6029b2d063988408061b7974.diff to "cherry-pick" 567460a602b4e2fc6029b2d063988408061b7974 (BF: explicitly mark train_test_split as not the one for nosetesting)
andy (8):
FIX manifold example - sorry, my bad.
COSMIT RST in manifold sphere example.
ENH fix random seed in manifold example
DOC added note in example that digits data is to small.
ENH Add "proximity" parameter to MDS.
FIX soime typos, modify test.
FIX another typo, fix examples
ENH updated to more examples.
bob (1):
Couple of small changes from comments
emanuele (1):
FIX: added logsumexp and nan_to_num to avoid underflows and NaNs
mr.Shu (9):
moved class_prior in NB to __init__
added deprecation warning to fit function
fixed docstring tests
fixed typos
added warnings
updated based on comments
fixed local variables
renamed the new parameter to class_wieght
fixed docstring test
syhw (13):
travis config file
update travis config
put the requirements at the right place
added requirements to travis config file
Merge https://github.com/scikit-learn/scikit-learn
Travis CI cfg + status in README + sklearn requirements
with Ubuntu's scipy instead of pip's
with python-nose
removed requirements.txt from travis cfg
removed requirements.txt
changed the build image URL in README for after pull-merge
trying travis cfg with system-site-packages
Merge https://github.com/scikit-learn/scikit-learn into travis
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