Version 0.13.1

February 23, 2013

The 0.13.1 release only fixes some bugs and does not add any new functionality.



List of contributors for release 0.13.1 by number of commits.

Version 0.13

January 21, 2013

New Estimator Classes


API changes summary

  • Renamed all occurrences of n_atoms to n_components for consistency. This applies to decomposition.DictionaryLearning, decomposition.MiniBatchDictionaryLearning, decomposition.dict_learning, decomposition.dict_learning_online.

  • Renamed all occurrences of max_iters to max_iter for consistency. This applies to semi_supervised.LabelPropagation and semi_supervised.label_propagation.LabelSpreading.

  • Renamed all occurrences of learn_rate to learning_rate for consistency in ensemble.BaseGradientBoosting and ensemble.GradientBoostingRegressor.

  • The module sklearn.linear_model.sparse is gone. Sparse matrix support was already integrated into the “regular” linear models.

  • sklearn.metrics.mean_square_error, which incorrectly returned the accumulated error, was removed. Use mean_squared_error instead.

  • Passing class_weight parameters to fit methods is no longer supported. Pass them to estimator constructors instead.

  • GMMs no longer have decode and rvs methods. Use the score, predict or sample methods instead.

  • The solver fit option in Ridge regression and classification is now deprecated and will be removed in v0.14. Use the constructor option instead.

  • feature_extraction.text.DictVectorizer now returns sparse matrices in the CSR format, instead of COO.

  • Renamed k in cross_validation.KFold and cross_validation.StratifiedKFold to n_folds, renamed n_bootstraps to n_iter in cross_validation.Bootstrap.

  • Renamed all occurrences of n_iterations to n_iter for consistency. This applies to cross_validation.ShuffleSplit, cross_validation.StratifiedShuffleSplit, utils.randomized_range_finder and utils.randomized_svd.

  • Replaced rho in linear_model.ElasticNet and linear_model.SGDClassifier by l1_ratio. The rho parameter had different meanings; l1_ratio was introduced to avoid confusion. It has the same meaning as previously rho in linear_model.ElasticNet and (1-rho) in linear_model.SGDClassifier.

  • linear_model.LassoLars and linear_model.Lars now store a list of paths in the case of multiple targets, rather than an array of paths.

  • The attribute gmm of hmm.GMMHMM was renamed to gmm_ to adhere more strictly with the API.

  • cluster.spectral_embedding was moved to manifold.spectral_embedding.

  • Renamed eig_tol in manifold.spectral_embedding, cluster.SpectralClustering to eigen_tol, renamed mode to eigen_solver.

  • Renamed mode in manifold.spectral_embedding and cluster.SpectralClustering to eigen_solver.

  • classes_ and n_classes_ attributes of tree.DecisionTreeClassifier and all derived ensemble models are now flat in case of single output problems and nested in case of multi-output problems.

  • The estimators_ attribute of ensemble.gradient_boosting.GradientBoostingRegressor and ensemble.gradient_boosting.GradientBoostingClassifier is now an array of :class:’tree.DecisionTreeRegressor’.

  • Renamed chunk_size to batch_size in decomposition.MiniBatchDictionaryLearning and decomposition.MiniBatchSparsePCA for consistency.

  • svm.SVC and svm.NuSVC now provide a classes_ attribute and support arbitrary dtypes for labels y. Also, the dtype returned by predict now reflects the dtype of y during fit (used to be np.float).

  • Changed default test_size in cross_validation.train_test_split to None, added possibility to infer test_size from train_size in cross_validation.ShuffleSplit and cross_validation.StratifiedShuffleSplit.

  • Renamed function sklearn.metrics.zero_one to sklearn.metrics.zero_one_loss. Be aware that the default behavior in sklearn.metrics.zero_one_loss is different from sklearn.metrics.zero_one: normalize=False is changed to normalize=True.

  • Renamed function metrics.zero_one_score to metrics.accuracy_score.

  • datasets.make_circles now has the same number of inner and outer points.

  • In the Naive Bayes classifiers, the class_prior parameter was moved from fit to __init__.


List of contributors for release 0.13 by number of commits.