[scikit-learn] annotated tag debian/0.13.1-1 created (now 57b998d)

[Andreas Tille]

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tille pushed a change to annotated tag debian/0.13.1-1
in repository scikit-learn.

        at  57b998d   (tag)
   tagging  efba14e15865b6ea6b10470aacff83d914a8607b (commit)
  replaces  debian/0.13-3
 tagged by  Yaroslav Halchenko
        on  Sat Jun 1 11:39:43 2013 -0400

- Log -----------------------------------------------------------------
Debian release 0.13.1-1
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Andreas Mueller (13):
      TST some more tests for multi output lars
      DOC fix typo in LinearSVC error message
      FIX make error message work when return_path=False
      TST fix random states in all dict learning tests, make test independent of test sequence.
      DOC add return values of cross_val_score and train_test_split to docstrings.
      ENH get rid of imports in test_common by checking by names, not classes.
      ENH break ties in OvO using scores
      ENH fix test_estimators_overwrite_params to test regressors and transformers
      TST stronger tests for arbitrary classes. make explicit what works and what doesn't.
      ENH set the random state to avoid heisenfailures
      COSMIT pep8
      DOC some copyediting
      REL increased version number, added whatsnew

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

Diego Molla (1):
      Minor bug fix in metrics.adjusted_rand_score

Gael Varoquaux (8):
      DOC: typo in warning
      BUG: reassignment_ratio == 0 in MiniBatchKmeans
      BUG: sparse center reassignment MiniBatchKMeans
      DOC: reference for discretise option
      COSMIT :: in rst is easier for syntax highlighters
      BUG: update joblib to 0.7.0d
      BUG: highly-degenerate roc curves
      DOC: add example and ref to lars_path in lasso_path

Gilles Louppe (1):
      DOC: add balance_weights to reference

Hrishikesh Huilgolkar (2):
      chi2 and additive_chi2 raise error if input are sparse matrices
      TST fit_transform(X)==fit(X).transform(X)

Lars Buitinck (16):
      WEB rm survey bar
      BUG move label_ from BaseLibSVM to BaseSVC
      COSMIT decouple regression and classification in SVMs
      COSMIT translate lgamma replacement to C and clean it up
      DOC update SMART notation in TfidfTransformer docs
      ENH refactor univariate feature selection
      DOC copyedit FeatureHasher narrative
      ENH move covtype loading to sklearn.datasets
      DOC pretty math in kernel docstrings
      BUG MinMaxScaler missing from preprocessing.__all__
      BUG fix broken grid search example
      BUG in KernelPCA: wrong default value for gamma
      ENH speed up RBFSampler by ~10%
      COSMIT update mailmap
      BUG in RadiusNeighborClassifier outlier handling
      ENH rewrite radius-NN classifier's outlier handling

Mathieu Blondel (1):
      DOC: make distinction between evaluation and pairwise metrics.

Nelle Varoquaux (1):
      DOC: small fix in the regression's score method documentation

Peter Prettenhofer (3):
      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

Rafael Cunha de Almeida (1):
      BUG MBKmeans only reassign centers if to_reassign.sum() > 1

Robert Marchman (5):
      raise ValueError for unfitted idf vector
      FIX docstring deletions
      ADD test coverage for _check_stop_list
      FIX comment typo
      TST improve feature_extraction.text coverage

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

Vlad Niculae (1):
      FIX: variable naming inconsistency in NMF

Yaroslav Halchenko (5):
      BF: explicitly mark train_test_split as not the one for nosetesting
      Merge tag '0.13.1' into releases
      Merge branch 'releases' into dfsg
      Merge commit '0.13.1-178-g9ad265e' into debian
      "Fresh" bugfix release: dropping all cherry picked changesets

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

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