diff --git a/doc/modules/classes.rst b/doc/modules/classes.rst
index 7275789c19a07cc600228a501b3fcaf20d8bf635..b41de5c108b5c6e0ac41ecf81f6077f9f01c77ee 100644
--- a/doc/modules/classes.rst
+++ b/doc/modules/classes.rst
@@ -724,8 +724,6 @@ Kernels:
linear_model.PassiveAggressiveClassifier
linear_model.PassiveAggressiveRegressor
linear_model.Perceptron
- linear_model.RandomizedLasso
- linear_model.RandomizedLogisticRegression
linear_model.RANSACRegressor
linear_model.Ridge
linear_model.RidgeClassifier
@@ -1392,6 +1390,18 @@ Recently deprecated
===================
+To be removed in 0.21
+---------------------
+
+.. autosummary::
+ :toctree: generated/
+ :template: deprecated_class.rst
+
+ linear_model.RandomizedLasso
+ linear_model.RandomizedLogisticRegression
+ neighbors.LSHForest
+
+
To be removed in 0.20
---------------------
diff --git a/doc/modules/pipeline.rst b/doc/modules/pipeline.rst
index b098ec04a999a112ae57744689d9899cf6c21cbf..4356b3fe8d640780cd984da5e65f5a2f423b094c 100644
--- a/doc/modules/pipeline.rst
+++ b/doc/modules/pipeline.rst
@@ -124,6 +124,8 @@ i.e. if the last estimator is a classifier, the :class:`Pipeline` can be used
as a classifier. If the last estimator is a transformer, again, so is the
pipeline.
+.. _pipeline_cache:
+
Caching transformers: avoid repeated computation
-------------------------------------------------
diff --git a/doc/whats_new.rst b/doc/whats_new.rst
index 1244c4596b741ab7057fe1c398fc82c755a1de6a..21eb3478dbc1bc6ed369967dde03f228d7b45044 100644
--- a/doc/whats_new.rst
+++ b/doc/whats_new.rst
@@ -10,6 +10,39 @@ Version 0.19
**In Development**
+Highlights
+----------
+
+We are excited to release a number of great new features including
+:class:`neighbors.LocalOutlierFactor` for anomaly detection,
+:class:`preprocessing.QuantileTransformer` for robust feature transformation,
+and the :class:`multioutput.ClassifierChain` meta-estimator to simply account
+for dependencies between classes in multilabel problems. We have some new
+algorithms in existing estimators, such as multiplicative update in
+:class:`decomposition.NMF` and multinomial
+:class:`linear_model.LogisticRegression` with L1 loss (use ``solver='saga'``).
+
+You can also learn faster. For instance, the :ref:`new option to cache
+transformations <pipeline_cache>` in :class:`pipeline.Pipeline` makes grid
+search over pipelines including slow transformations much more efficient. And
+you can predict faster: if you're sure you know what you're doing, you can turn
+off validating that the input is finite using :func:`config_context`.
+
+Cross validation is now able to return the results from multiple metric
+evaluations. The new :func:`model_selection.cross_validate` can return many
+scores on the test data as well as training set performance and timings, and we
+have extended the ``scoring`` and ``refit`` parameters for grid/randomized
+search :ref:`to handle multiple metrics <multimetric_grid_search>`.
+
+We've made some important fixes too. We've fixed a longstanding implementation
+erorr in :func:`metrics.average_precision_score`, so please be cautious with
+prior results reported from that function. A number of errors in the
+:class:`manifold.TSNE` implementation have been fixed, particularly in the
+default Barnes-Hut approximation. :class:`semi_supervised.LabelSpreading` and
+:class:`semi_supervised.LabelPropagation` have had substantial fixes.
+LabelPropagation was previously broken. LabelSpreading should now correctly
+respect its alpha parameter.
+
Changed models
--------------
@@ -18,8 +51,21 @@ parameters, may produce different models from the previous version. This often
occurs due to changes in the modelling logic (bug fixes or enhancements), or in
random sampling procedures.
- * :class:`sklearn.ensemble.IsolationForest` (bug fix)
- * :class:`sklearn.manifold.TSNE` (bug fix)
+ * :class:`cluster.KMeans` with sparse X and initial centroids given (bug fix)
+ * :class:`cross_decomposition.PLSRegression`
+ with ``scale=True`` (bug fix)
+ * :class:`ensemble.GradientBoostingClassifier` and
+ :class:`ensemble.GradientBoostingRegressor` where ``min_impurity_split`` is used (bug fix)
+ * gradient boosting ``loss='quantile'`` (bug fix)
+ * :class:`ensemble.IsolationForest` (bug fix)
+ * :class:`feature_selection.SelectFdr` (bug fix)
+ * :class:`linear_model.RANSACRegressor` (bug fix)
+ * :class:`linear_model.LassoLars` (bug fix)
+ * :class:`linear_model.LassoLarsIC` (bug fix)
+ * :class:`manifold.TSNE` (bug fix)
+ * :class:`semi_supervised.LabelSpreading` (bug fix)
+ * :class:`semi_supervised.LabelPropagation` (bug fix)
+ * tree based models where ``min_weight_fraction_leaf`` is used (enhancement)
Details are listed in the changelog below.
@@ -32,101 +78,81 @@ Changelog
New features
............
- - :class:`model_selection.GridSearchCV` and
- :class:`model_selection.RandomizedSearchCV` now support simultaneous
- evaluation of multiple metrics. Refer to the
- :ref:`multimetric_grid_search` section of the user guide for more
- information. :issue:`7388` by `Raghav RV`_
+Classifiers and regressors
- - Added the :func:`model_selection.cross_validate` which allows evaluation
- of multiple metrics. This function returns a dict with more useful
- information from cross-validation such as the train scores, fit times and
- score times.
- Refer to :ref:`multimetric_cross_validation` section of the userguide
- for more information. :issue:`7388` by `Raghav RV`_
-
- Added :class:`multioutput.ClassifierChain` for multi-label
classification. By `Adam Kleczewski <adamklec>`_.
- - Validation that input data contains no NaN or inf can now be suppressed
- using :func:`config_context`, at your own risk. This will save on runtime,
- and may be particularly useful for prediction time. :issue:`7548` by
- `Joel Nothman`_.
+ - Added solver ``'saga'`` that implements the improved version of Stochastic
+ Average Gradient, in :class:`linear_model.LogisticRegression` and
+ :class:`linear_model.Ridge`. It allows the use of L1 penalty with
+ multinomial logistic loss, and behaves marginally better than 'sag'
+ during the first epochs of ridge and logistic regression.
+ :issue:`8446` by `Arthur Mensch`_.
+
+Other estimators
- Added the :class:`neighbors.LocalOutlierFactor` class for anomaly
detection based on nearest neighbors.
:issue:`5279` by `Nicolas Goix`_ and `Alexandre Gramfort`_.
+ - Added :class:`preprocessing.QuantileTransformer` class and
+ :func:`preprocessing.quantile_transform` function for features
+ normalization based on quantiles.
+ :issue:`8363` by :user:`Denis Engemann <dengemann>`,
+ :user:`Guillaume Lemaitre <glemaitre>`, `Olivier Grisel`_, `Raghav RV`_,
+ :user:`Thierry Guillemot <tguillemot>`, and `Gael Varoquaux`_.
+
- The new solver ``'mu'`` implements a Multiplicate Update in
:class:`decomposition.NMF`, allowing the optimization of all
beta-divergences, including the Frobenius norm, the generalized
Kullback-Leibler divergence and the Itakura-Saito divergence.
:issue:`5295` by `Tom Dupre la Tour`_.
- - Added the :class:`model_selection.RepeatedKFold` and
- :class:`model_selection.RepeatedStratifiedKFold`.
- :issue:`8120` by `Neeraj Gangwar`_.
+Model selection and evaluation
+
+ - :class:`model_selection.GridSearchCV` and
+ :class:`model_selection.RandomizedSearchCV` now support simultaneous
+ evaluation of multiple metrics. Refer to the
+ :ref:`multimetric_grid_search` section of the user guide for more
+ information. :issue:`7388` by `Raghav RV`_
+
+ - Added the :func:`model_selection.cross_validate` which allows evaluation
+ of multiple metrics. This function returns a dict with more useful
+ information from cross-validation such as the train scores, fit times and
+ score times.
+ Refer to :ref:`multimetric_cross_validation` section of the userguide
+ for more information. :issue:`7388` by `Raghav RV`_
- Added :func:`metrics.mean_squared_log_error`, which computes
the mean square error of the logarithmic transformation of targets,
particularly useful for targets with an exponential trend.
:issue:`7655` by :user:`Karan Desai <karandesai-96>`.
- - Added solver ``'saga'`` that implements the improved version of Stochastic
- Average Gradient, in :class:`linear_model.LogisticRegression` and
- :class:`linear_model.Ridge`. It allows the use of L1 penalty with
- multinomial logistic loss, and behaves marginally better than 'sag'
- during the first epochs of ridge and logistic regression.
- :issue:`8446` by `Arthur Mensch`_.
-
- - Added :class:`preprocessing.QuantileTransformer` class and
- :func:`preprocessing.quantile_transform` function for features
- normalization based on quantiles.
- :issue:`8363` by :user:`Denis Engemann <dengemann>`,
- :user:`Guillaume Lemaitre <glemaitre>`, `Olivier Grisel`_, `Raghav RV`_,
- :user:`Thierry Guillemot <tguillemot>`, and `Gael Varoquaux`_.
-
- Added :func:`metrics.dcg_score` and :func:`metrics.ndcg_score`, which
compute Discounted cumulative gain (DCG) and Normalized discounted
cumulative gain (NDCG).
:issue:`7739` by :user:`David Gasquez <davidgasquez>`.
-Enhancements
-............
+ - Added the :class:`model_selection.RepeatedKFold` and
+ :class:`model_selection.RepeatedStratifiedKFold`.
+ :issue:`8120` by `Neeraj Gangwar`_.
- - :func:`metrics.matthews_corrcoef` now support multiclass classification.
- :issue:`8094` by :user:`Jon Crall <Erotemic>`.
- - Update Sphinx-Gallery from 0.1.4 to 0.1.7 for resolving links in
- documentation build with Sphinx>1.5 :issue:`8010`, :issue:`7986` by
- :user:`Oscar Najera <Titan-C>`
- - :class:`multioutput.MultiOutputRegressor` and :class:`multioutput.MultiOutputClassifier`
- now support online learning using `partial_fit`.
- issue: `8053` by :user:`Peng Yu <yupbank>`.
- - :class:`pipeline.Pipeline` allows to cache transformers
- within a pipeline by using the ``memory`` constructor parameter.
- :issue:`7990` by :user:`Guillaume Lemaitre <glemaitre>`.
+Miscellaneous
- - :class:`decomposition.PCA`, :class:`decomposition.IncrementalPCA` and
- :class:`decomposition.TruncatedSVD` now expose the singular values
- from the underlying SVD. They are stored in the attribute
- ``singular_values_``, like in :class:`decomposition.IncrementalPCA`.
+ - Validation that input data contains no NaN or inf can now be suppressed
+ using :func:`config_context`, at your own risk. This will save on runtime,
+ and may be particularly useful for prediction time. :issue:`7548` by
+ `Joel Nothman`_.
- - :class:`cluster.MiniBatchKMeans` and :class:`cluster.KMeans`
- now uses significantly less memory when assigning data points to their
- nearest cluster center. :issue:`7721` by :user:`Jon Crall <Erotemic>`.
+ - Added a test to ensure parameter listing in docstrings match the
+ function/class signature. :issue:`9206` by `Alexandre Gramfort`_ and
+ `Raghav RV`_.
- - Added ``classes_`` attribute to :class:`model_selection.GridSearchCV`,
- :class:`model_selection.RandomizedSearchCV`, :class:`grid_search.GridSearchCV`,
- and :class:`grid_search.RandomizedSearchCV` that matches the ``classes_``
- attribute of ``best_estimator_``. :issue:`7661` and :issue:`8295`
- by :user:`Alyssa Batula <abatula>`, :user:`Dylan Werner-Meier <unautre>`,
- and :user:`Stephen Hoover <stephen-hoover>`.
+Enhancements
+............
- - Relax assumption on the data for the
- :class:`kernel_approximation.SkewedChi2Sampler`. Since the Skewed-Chi2
- kernel is defined on the open interval :math:`(-skewedness; +\infty)^d`,
- the transform function should not check whether ``X < 0`` but whether ``X <
- -self.skewedness``. :issue:`7573` by :user:`Romain Brault <RomainBrault>`.
+Trees and ensembles
- The ``min_weight_fraction_leaf`` constraint in tree construction is now
more efficient, taking a fast path to declare a node a leaf if its weight
@@ -134,47 +160,32 @@ Enhancements
different from previous versions where ``min_weight_fraction_leaf`` is
used. :issue:`7441` by :user:`Nelson Liu <nelson-liu>`.
- - Added ``average`` parameter to perform weights averaging in
- :class:`linear_model.PassiveAggressiveClassifier`. :issue:`4939`
- by :user:`Andrea Esuli <aesuli>`.
-
- - Custom metrics for the :mod:`sklearn.neighbors` binary trees now have
- fewer constraints: they must take two 1d-arrays and return a float.
- :issue:`6288` by `Jake Vanderplas`_.
-
- :class:`ensemble.GradientBoostingClassifier` and :class:`ensemble.GradientBoostingRegressor`
now support sparse input for prediction.
:issue:`6101` by :user:`Ibraim Ganiev <olologin>`.
- - Added ``shuffle`` and ``random_state`` parameters to shuffle training
- data before taking prefixes of it based on training sizes in
- :func:`model_selection.learning_curve`.
- :issue:`7506` by :user:`Narine Kokhlikyan <NarineK>`.
+ - :class:`ensemble.VotingClassifier` now allows changing estimators by using
+ :meth:`ensemble.VotingClassifier.set_params`. An estimator can also be
+ removed by setting it to ``None``.
+ :issue:`7674` by :user:`Yichuan Liu <yl565>`.
- - Added ``norm_order`` parameter to :class:`feature_selection.SelectFromModel`
- to enable selection of the norm order when ``coef_`` is more than 1D.
- :issue:`6181` by :user:`Antoine Wendlinger <antoinewdg>`.
+ - :func:`tree.export_graphviz` now shows configurable number of decimal
+ places. :issue:`8698` by :user:`Guillaume Lemaitre <glemaitre>`.
- - Added ``sample_weight`` parameter to :meth:`pipeline.Pipeline.score`.
- :issue:`7723` by :user:`Mikhail Korobov <kmike>`.
-
- - ``check_estimator`` now attempts to ensure that methods transform, predict, etc.
- do not set attributes on the estimator.
- :issue:`7533` by :user:`Ekaterina Krivich <kiote>`.
+Linear, kernelized and related models
- :class:`linear_model.SGDClassifier`, :class:`linear_model.SGDRegressor`,
:class:`linear_model.PassiveAggressiveClassifier`,
:class:`linear_model.PassiveAggressiveRegressor` and
- :class:`linear_model.Perceptron` now expose a ``max_iter`` and
+ :class:`linear_model.Perceptron` now expose ``max_iter`` and
``tol`` parameters, to handle convergence more precisely.
``n_iter`` parameter is deprecated, and the fitted estimator exposes
a ``n_iter_`` attribute, with actual number of iterations before
- convergence. By `Tom Dupre la Tour`_.
+ convergence. :issue:`5036` by `Tom Dupre la Tour`_.
- - For sparse matrices, :func:`preprocessing.normalize` with ``return_norm=True``
- will now raise a ``NotImplementedError`` with 'l1' or 'l2' norm and with
- norm 'max' the norms returned will be the same as for dense matrices.
- :issue:`7771` by `Ang Lu <https://github.com/luang008>`_.
+ - Added ``average`` parameter to perform weight averaging in
+ :class:`linear_model.PassiveAggressiveClassifier`. :issue:`4939`
+ by :user:`Andrea Esuli <aesuli>`.
- :class:`linear_model.RANSACRegressor` no longer throws an error
when calling ``fit`` if no inliers are found in its first iteration.
@@ -182,173 +193,291 @@ Enhancements
attributes, ``n_skips_*``.
:issue:`7914` by :user:`Michael Horrell <mthorrell>`.
- - :func:`model_selection.cross_val_predict` now returns output of the
- correct shape for all values of the argument ``method``.
- :issue:`7863` by :user:`Aman Dalmia <dalmia>`.
+ - In :class:`gaussian_process.GaussianProcessRegressor`, method ``predict``
+ is a lot faster with ``return_std=True``. :issue:`8591` by
+ :user:`Hadrien Bertrand <hbertrand>`.
- - Fix a bug where :class:`feature_selection.SelectFdr` did not
- exactly implement Benjamini-Hochberg procedure. It formerly may have
- selected fewer features than it should.
- :issue:`7490` by :user:`Peng Meng <mpjlu>`.
+ - Added ``return_std`` to ``predict`` method of
+ :class:`linear_model.ARDRegression` and
+ :class:`linear_model.BayesianRidge`.
+ :issue:`7838` by :user:`Sergey Feldman <sergeyf>`.
- - Added ability to set ``n_jobs`` parameter to :func:`pipeline.make_union`.
- A ``TypeError`` will be raised for any other kwargs. :issue:`8028`
- by :user:`Alexander Booth <alexandercbooth>`.
+ - Memory usage enhancements: Prevent cast from float32 to float64 in:
+ :class:`linear_model.MultiTaskElasticNet`;
+ :class:`linear_model.LogisticRegression` when using newton-cg solver; and
+ :class:`linear_model.Ridge` when using svd, sparse_cg, cholesky or lsqr
+ solvers. :issue:`8835`, :issue:`8061` by :user:`Joan Massich <massich>` and :user:`Nicolas
+ Cordier <ncordier>` and :user:`Thierry Guillemot`.
- - Added type checking to the ``accept_sparse`` parameter in
- :mod:`sklearn.utils.validation` methods. This parameter now accepts only
- boolean, string, or list/tuple of strings. ``accept_sparse=None`` is deprecated
- and should be replaced by ``accept_sparse=False``.
- :issue:`7880` by :user:`Josh Karnofsky <jkarno>`.
+Other predictors
- - :class:`model_selection.GridSearchCV`, :class:`model_selection.RandomizedSearchCV`
- and :func:`model_selection.cross_val_score` now allow estimators with callable
- kernels which were previously prohibited. :issue:`8005` by `Andreas Müller`_ .
+ - Custom metrics for the :mod:`neighbors` binary trees now have
+ fewer constraints: they must take two 1d-arrays and return a float.
+ :issue:`6288` by `Jake Vanderplas`_.
- - Added ability to use sparse matrices in :func:`feature_selection.f_regression`
- with ``center=True``. :issue:`8065` by :user:`Daniel LeJeune <acadiansith>`.
+ - ``algorithm='auto`` in :mod:`neighbors` estimators now chooses the most
+ appropriate algorithm for all input types and metrics. :issue:`9145` by
+ :user:`Herilalaina Rakotoarison <herilalaina>` and :user:`Reddy Chinthala
+ <preddy5Pradyumna>`.
- - Add ``sample_weight`` parameter to :func:`metrics.cohen_kappa_score`.
- :issue:`8335` by :user:`Victor Poughon <vpoughon>`.
+Decomposition, manifold learning and clustering
- - In :class:`gaussian_process.GaussianProcessRegressor`, method ``predict``
- is a lot faster with ``return_std=True``. :issue:`8591` by
- :user:`Hadrien Bertrand <hbertrand>`.
+ - :class:`cluster.MiniBatchKMeans` and :class:`cluster.KMeans`
+ now use significantly less memory when assigning data points to their
+ nearest cluster center. :issue:`7721` by :user:`Jon Crall <Erotemic>`.
- - Added ability to use sparse matrices in :func:`feature_selection.f_regression`
- with ``center=True``. :issue:`8065` by :user:`Daniel LeJeune <acadiansith>`.
+ - :class:`decomposition.PCA`, :class:`decomposition.IncrementalPCA` and
+ :class:`decomposition.TruncatedSVD` now expose the singular values
+ from the underlying SVD. They are stored in the attribute
+ ``singular_values_``, like in :class:`decomposition.IncrementalPCA`.
+ :issue:`7685` by :user:`Tommy Löfstedt <tomlof>`
- - :class:`ensemble.VotingClassifier` now allow changing estimators by using
- :meth:`ensemble.VotingClassifier.set_params`. Estimators can also be
- removed by setting it to `None`.
- :issue:`7674` by :user:`Yichuan Liu <yl565>`.
+ - :class:`decomposition.NMF` now faster when ``beta_loss=0``.
+ :issue:`9277` by :user:`hongkahjun`.
- - Prevent cast from float32 to float64 in
- :class:`linear_model.LogisticRegression` when using newton-cg
- solver. :issue:`8835` by :user:`Joan Massich <massich>`.
+ - Memory improvements for method ``barnes_hut`` in :class:`manifold.TSNE`
+ :issue:`7089` by :user:`Thomas Moreau <tomMoral>` and `Olivier Grisel`_.
- - Prevent cast from float32 to float64 in
- :class:`linear_model.Ridge` when using svd, sparse_cg, cholesky or lsqr solvers
- :class:`sklearn.linear_model.Ridge` when using svd, sparse_cg, cholesky or lsqr solvers
- by :user:`Joan Massich <massich>`, :user:`Nicolas Cordier <ncordier>`
+ - Optimization schedule improvements for Barnes-Hut :class:`manifold.TSNE`
+ so the results are closer to the one from the reference implementation
+ `lvdmaaten/bhtsne <https://github.com/lvdmaaten/bhtsne>`_ by :user:`Thomas
+ Moreau <tomMoral>` and `Olivier Grisel`_.
- - Add ``max_train_size`` parameter to :class:`model_selection.TimeSeriesSplit`
- :issue:`8282` by :user:`Aman Dalmia <dalmia>`.
+ - Memory usage enhancements: Prevent cast from float32 to float64 in
+ :class:`decomposition.PCA` and
+ :func:`decomposition.randomized_svd_low_rank`.
+ :issue:`9067` by `Raghav RV`_.
- - Make it possible to load a chunk of an svmlight formatted file by
- passing a range of bytes to :func:`datasets.load_svmlight_file`.
- :issue:`935` by :user:`Olivier Grisel <ogrisel>`.
+Preprocessing and feature selection
+
+ - Added ``norm_order`` parameter to :class:`feature_selection.SelectFromModel`
+ to enable selection of the norm order when ``coef_`` is more than 1D.
+ :issue:`6181` by :user:`Antoine Wendlinger <antoinewdg>`.
+
+ - Added ability to use sparse matrices in :func:`feature_selection.f_regression`
+ with ``center=True``. :issue:`8065` by :user:`Daniel LeJeune <acadiansith>`.
- Small performance improvement to n-gram creation in
:mod:`feature_extraction.text` by binding methods for loops and
- special-casing unigrams. :issue:`7567` by `Jaye Doepke <jtdoepke>`
+ special-casing unigrams. :issue:`7567` by :user:`Jaye Doepke <jtdoepke>`
+
+ - Relax assumption on the data for the
+ :class:`kernel_approximation.SkewedChi2Sampler`. Since the Skewed-Chi2
+ kernel is defined on the open interval :math:`(-skewedness; +\infty)^d`,
+ the transform function should not check whether ``X < 0`` but whether ``X <
+ -self.skewedness``. :issue:`7573` by :user:`Romain Brault <RomainBrault>`.
+
+ - Made default kernel parameters kernel-dependent in
+ :class:`kernel_approximation.Nystroem`.
+ :issue:`5229` by :user:`Saurabh Bansod <mth4saurabh>` and `Andreas Müller`_.
+
+Model evaluation and meta-estimators
+
+ - :class:`pipeline.Pipeline` is now able to cache transformers
+ within a pipeline by using the ``memory`` constructor parameter.
+ :issue:`7990` by :user:`Guillaume Lemaitre <glemaitre>`.
+
+ - :class:`pipeline.Pipeline` steps can now be accessed as attributes of its
+ ``named_steps`` attribute. :issue:`8586` by :user:`Herilalaina
+ Rakotoarison <herilalaina>`.
+
+ - Added ``sample_weight`` parameter to :meth:`pipeline.Pipeline.score`.
+ :issue:`7723` by :user:`Mikhail Korobov <kmike>`.
+
+ - Added ability to set ``n_jobs`` parameter to :func:`pipeline.make_union`.
+ A ``TypeError`` will be raised for any other kwargs. :issue:`8028`
+ by :user:`Alexander Booth <alexandercbooth>`.
+
+ - :class:`model_selection.GridSearchCV`,
+ :class:`model_selection.RandomizedSearchCV` and
+ :func:`model_selection.cross_val_score` now allow estimators with callable
+ kernels which were previously prohibited.
+ :issue:`8005` by `Andreas Müller`_ .
+
+ - :func:`model_selection.cross_val_predict` now returns output of the
+ correct shape for all values of the argument ``method``.
+ :issue:`7863` by :user:`Aman Dalmia <dalmia>`.
+
+ - Added ``shuffle`` and ``random_state`` parameters to shuffle training
+ data before taking prefixes of it based on training sizes in
+ :func:`model_selection.learning_curve`.
+ :issue:`7506` by :user:`Narine Kokhlikyan <NarineK>`.
+
+ - :class:`model_selection.StratifiedShuffleSplit` now works with multioutput
+ multiclass (or multilabel) data. :issue:`9044` by `Vlad Niculae`_.
- Speed improvements to :class:`model_selection.StratifiedShuffleSplit`.
:issue:`5991` by :user:`Arthur Mensch <arthurmensch>` and `Joel Nothman`_.
- - Memory improvements for method barnes_hut in :class:`manifold.TSNE`
- :issue:`7089` by :user:`Thomas Moreau <tomMoral>` and `Olivier Grisel`_.
+ - Add ``shuffle`` parameter to :func:`model_selection.train_test_split`.
+ :issue:`8845` by :user:`themrmax <themrmax>`
+
+ - :class:`multioutput.MultiOutputRegressor` and :class:`multioutput.MultiOutputClassifier`
+ now support online learning using ``partial_fit``.
+ :issue: `8053` by :user:`Peng Yu <yupbank>`.
+
+ - Add ``max_train_size`` parameter to :class:`model_selection.TimeSeriesSplit`
+ :issue:`8282` by :user:`Aman Dalmia <dalmia>`.
+
+ - More clustering metrics are now available through :func:`metrics.get_scorer`
+ and ``scoring`` parameters. :issue:`8117` by `Raghav RV`_.
- - Optimization schedule improvements for so the results are closer to the
- one from the reference implementation
- `lvdmaaten/bhtsne <https://github.com/lvdmaaten/bhtsne>`_ by
- :user:`Thomas Moreau <tomMoral>` and `Olivier Grisel`_.
+Metrics
+
+ - :func:`metrics.matthews_corrcoef` now support multiclass classification.
+ :issue:`8094` by :user:`Jon Crall <Erotemic>`.
+
+ - Add ``sample_weight`` parameter to :func:`metrics.cohen_kappa_score`.
+ :issue:`8335` by :user:`Victor Poughon <vpoughon>`.
+
+Miscellaneous
+
+ - :func:`utils.check_estimator` now attempts to ensure that methods
+ transform, predict, etc. do not set attributes on the estimator.
+ :issue:`7533` by :user:`Ekaterina Krivich <kiote>`.
+
+ - Added type checking to the ``accept_sparse`` parameter in
+ :mod:`utils.validation` methods. This parameter now accepts only boolean,
+ string, or list/tuple of strings. ``accept_sparse=None`` is deprecated and
+ should be replaced by ``accept_sparse=False``.
+ :issue:`7880` by :user:`Josh Karnofsky <jkarno>`.
+
+ - Make it possible to load a chunk of an svmlight formatted file by
+ passing a range of bytes to :func:`datasets.load_svmlight_file`.
+ :issue:`935` by :user:`Olivier Grisel <ogrisel>`.
+
+ - :class:`dummy.DummyClassifier` and :class:`dummy.DummyRegressor`
+ now accept non-finite features. :issue:`8931` by :user:`Attractadore`.
Bug fixes
.........
- - :func:`metrics.average_precision_score` no longer linearly
- interpolates between operating points, and instead weighs precisions
- by the change in recall since the last operating point, as per the
- `Wikipedia entry <http://en.wikipedia.org/wiki/Average_precision>`_.
- (`#7356 <https://github.com/scikit-learn/scikit-learn/pull/7356>`_). By
- :user:`Nick Dingwall <ndingwall>` and `Gael Varoquaux`_.
+Trees and ensembles
- - Fixed a bug in :class:`covariance.MinCovDet` where inputting data
- that produced a singular covariance matrix would cause the helper method
- ``_c_step`` to throw an exception.
- :issue:`3367` by :user:`Jeremy Steward <ThatGeoGuy>`
+ - Fixed a memory leak in trees when using trees with ``criterion='mae'``.
+ :issue:`8002` by `Raghav RV`_.
- Fixed a bug where :class:`ensemble.IsolationForest` uses an
an incorrect formula for the average path length
:issue:`8549` by `Peter Wang <https://github.com/PTRWang>`_.
- - Fixed a bug where :class:`cluster.DBSCAN` gives incorrect
- result when input is a precomputed sparse matrix with initial
- rows all zero. :issue:`8306` by :user:`Akshay Gupta <Akshay0724>`
-
- Fixed a bug where :class:`ensemble.AdaBoostClassifier` throws
``ZeroDivisionError`` while fitting data with single class labels.
:issue:`7501` by :user:`Dominik Krzeminski <dokato>`.
- - Fixed a bug when :func:`datasets.make_classification` fails
- when generating more than 30 features. :issue:`8159` by
- :user:`Herilalaina Rakotoarison <herilalaina>`.
+ - Fixed a bug in :class:`ensemble.GradientBoostingClassifier` and
+ :class:`ensemble.GradientBoostingRegressor` where a float being compared
+ to ``0.0`` using ``==`` caused a divide by zero error. :issue:`7970` by
+ :user:`He Chen <chenhe95>`.
- - Fixed a bug where :func:`model_selection.BaseSearchCV.inverse_transform`
- returns ``self.best_estimator_.transform()`` instead of
- ``self.best_estimator_.inverse_transform()``.
- :issue:`8344` by :user:`Akshay Gupta <Akshay0724>`.
+ - Fix a bug where :class:`ensemble.GradientBoostingClassifier` and
+ :class:`ensemble.GradientBoostingRegressor` ignored the
+ ``min_impurity_split`` parameter.
+ :issue:`8006` by :user:`Sebastian Pölsterl <sebp>`.
- - Fixed same issue in :func:`grid_search.BaseSearchCV.inverse_transform`
- :issue:`8846` by :user:`Rasmus Eriksson <MrMjauh>`
+ - Fixed ``oob_score`` in :class:`ensemble.BaggingClassifier`.
+ :issue:`8936` by :user:`Michael Lewis <mlewis1729>`
- - Fixed a bug where :class:`linear_model.RandomizedLasso` and
- :class:`linear_model.RandomizedLogisticRegression` breaks for
- sparse input. :issue:`8259` by :user:`Aman Dalmia <dalmia>`.
+ - Fixed excessive memory usage in prediction for random forests estimators.
+ :issue:`8672` by :user:`Mike Benfield <mikebenfield>`.
- - Fixed a bug where :func:`linear_model.RANSACRegressor.fit` may run until
- ``max_iter`` if finds a large inlier group early. :issue:`8251` by :user:`aivision2020`.
+ - Fixed a bug where ``sample_weight`` as a list broke random forests in Python 2
+ :issue:`8068` by :user:`xor`.
- - Fixed a bug where :class:`sklearn.naive_bayes.MultinomialNB` and :class:`sklearn.naive_bayes.BernoulliNB`
- failed when `alpha=0`. :issue:`5814` by :user:`Yichuan Liu <yl565>` and
- :user:`Herilalaina Rakotoarison <herilalaina>`.
+ - Fixed a bug where :class:`ensemble.IsolationForest` fails when
+ ``max_features`` is less than 1.
+ :issue:`5732` by :user:`Ishank Gulati <IshankGulati>`.
- - Fixed a bug where :func:`datasets.make_moons` gives an
- incorrect result when ``n_samples`` is odd.
- :issue:`8198` by :user:`Josh Levy <levy5674>`.
+ - Fix a bug where gradient boosting with ``loss='quantile'`` computed
+ negative errors for negative values of ``ytrue - ypred`` leading to wrong
+ values when calling ``__call__``.
+ :issue:`8087` by :user:`Alexis Mignon <AlexisMignon>`
+
+ - Fix a bug where :class:`ensemble.VotingClassifier` raises an error
+ when a numpy array is passed in for weights. :issue:`7983` by
+ :user:`Vincent Pham <vincentpham1991>`.
+
+ - Fixed a bug where :func:`tree.export_graphviz` raised an error
+ when the length of features_names does not match n_features in the decision
+ tree. :issue:`8512` by :user:`Li Li <aikinogard>`.
+
+Linear, kernelized and related models
+
+ - Fixed a bug where :func:`linear_model.RANSACRegressor.fit` may run until
+ ``max_iter`` if it finds a large inlier group early. :issue:`8251` by
+ :user:`aivision2020`.
+
+ - Fixed a bug where :class:`naive_bayes.MultinomialNB` and
+ :class:`naive_bayes.BernoulliNB` failed when ``alpha=0``. :issue:`5814` by
+ :user:`Yichuan Liu <yl565>` and :user:`Herilalaina Rakotoarison
+ <herilalaina>`.
- Fixed a bug where :class:`linear_model.LassoLars` does not give
the same result as the LassoLars implementation available
in R (lars library). :issue:`7849` by :user:`Jair Montoya Martinez <jmontoyam>`.
- - Some ``fetch_`` functions in :mod:`sklearn.datasets` were ignoring the
- ``download_if_missing`` keyword. :issue:`7944` by :user:`Ralf Gommers <rgommers>`.
+ - Fixed a bug in :class:`linear_model.RandomizedLasso`,
+ :class:`linear_model.Lars`, :class:`linear_model.LassoLars`,
+ :class:`linear_model.LarsCV` and :class:`linear_model.LassoLarsCV`,
+ where the parameter ``precompute`` was not used consistently across
+ classes, and some values proposed in the docstring could raise errors.
+ :issue:`5359` by `Tom Dupre la Tour`_.
- - Fixed a bug in :class:`ensemble.GradientBoostingClassifier`
- and :class:`ensemble.GradientBoostingRegressor`
- where a float being compared to ``0.0`` using ``==`` caused a divide by zero
- error. issue:`7970` by :user:`He Chen <chenhe95>`.
+ - Fix inconsistent results between :class:`linear_model.RidgeCV` and
+ :class:`linear_model.Ridge` when using ``normalize=True``. :issue:`9302`
+ by `Alexandre Gramfort`_.
- - Fix a bug regarding fitting :class:`cluster.KMeans` with a sparse
- array X and initial centroids, where X's means were unnecessarily being
- subtracted from the centroids. :issue:`7872` by :user:`Josh Karnofsky <jkarno>`.
+ - Fix a bug where :func:`linear_model.LassoLars.fit` sometimes
+ left ``coef_`` as a list, rather than an ndarray.
+ :issue:`8160` by :user:`CJ Carey <perimosocordiae>`.
- - Fix estimators to accept a ``sample_weight`` parameter of type
- ``pandas.Series`` in their ``fit`` function. :issue:`7825` by
- `Kathleen Chen`_.
+ - Fix :func:`linear_model.BayesianRidge.fit` to return
+ ridge parameter ``alpha_`` and ``lambda_`` consistent with calculated
+ coefficients ``coef_`` and ``intercept_``.
+ :issue:`8224` by :user:`Peter Gedeck <gedeck>`.
- - Fixed a bug where :class:`ensemble.IsolationForest` fails when
- ``max_features`` is less than 1.
- :issue:`5732` by :user:`Ishank Gulati <IshankGulati>`.
+ - Fixed a bug in :class:`svm.OneClassSVM` where it returned floats instead of
+ integer classes. :issue:`8676` by :user:`Vathsala Achar <VathsalaAchar>`.
- - Fix a bug where :class:`ensemble.VotingClassifier` raises an error
- when a numpy array is passed in for weights. :issue:`7983` by
- :user:`Vincent Pham <vincentpham1991>`.
+ - Fix AIC/BIC criterion computation in :class:`linear_model.LassoLarsIC`.
+ :issue:`9022` by `Alexandre Gramfort`_ and :user:`Mehmet Basbug <mehmetbasbug>`.
+
+ - Fixed a memory leak in our LibLinear implementation. :issue:`9024` by
+ :user:`Sergei Lebedev <superbobry>`
+
+ - Fix bug where stratified CV splitters did not work with
+ :class:`linear_model.LassoCV`. :issue:`8973` by
+ :user:`Paulo Haddad <paulochf>`.
+
+ - Fixed a bug in :class:`gaussian_process.GaussianProcessRegressor`
+ when the standard deviation and covariance predicted without fit
+ would fail with a unmeaningful error by default.
+ :issue:`6573` by :user:`Quazi Marufur Rahman <qmaruf>` and
+ `Manoj Kumar`_.
+
+Other predictors
+
+ - Fix :class:`semi_supervised.BaseLabelPropagation` to correctly implement
+ ``LabelPropagation`` and ``LabelSpreading`` as done in the referenced
+ papers. :issue:`9239`
+ by :user:`Andre Ambrosio Boechat <boechat107>`, :user:`Utkarsh Upadhyay
+ <musically-ut>`, and `Joel Nothman`_.
+
+Decomposition, manifold learning and clustering
+
+ - Fixed the implementation of :class:`manifold.TSNE`:
+ - ``early_exageration`` parameter had no effect and is now used for the
+ first 250 optimization iterations.
+ - Fixed the ``InsersionError`` reported in :issue:`8992`.
+ - Improve the learning schedule to match the one from the reference
+ implementation `lvdmaaten/bhtsne <https://github.com/lvdmaaten/bhtsne>`_.
+ by :user:`Thomas Moreau <tomMoral>` and `Olivier Grisel`_.
- Fix a bug in :class:`decomposition.LatentDirichletAllocation`
where the ``perplexity`` method was returning incorrect results because
the ``transform`` method returns normalized document topic distributions
as of version 0.18. :issue:`7954` by :user:`Gary Foreman <garyForeman>`.
- - Fix a bug where :class:`ensemble.GradientBoostingClassifier` and
- :class:`ensemble.GradientBoostingRegressor` ignored the
- ``min_impurity_split`` parameter.
- :issue:`8006` by :user:`Sebastian Pölsterl <sebp>`.
-
- - Fixes to the input validation in :class:`covariance.EllipticEnvelope`.
- :issue:`8086` by `Andreas Müller`_.
-
- Fix output shape and bugs with n_jobs > 1 in
:class:`decomposition.SparseCoder` transform and
:func:`decomposition.sparse_encode`
@@ -356,158 +485,208 @@ Bug fixes
This also impacts the output shape of :class:`decomposition.DictionaryLearning`.
:issue:`8086` by `Andreas Müller`_.
+ - Fixed the implementation of ``explained_variance_``
+ in :class:`decomposition.PCA`,
+ :class:`decomposition.RandomizedPCA` and
+ :class:`decomposition.IncrementalPCA`.
+ :issue:`9105` by `Hanmin Qin <https://github.com/qinhanmin2014>`_.
+
+ - Fixed a bug where :class:`cluster.DBSCAN` gives incorrect
+ result when input is a precomputed sparse matrix with initial
+ rows all zero. :issue:`8306` by :user:`Akshay Gupta <Akshay0724>`
+
+ - Fix a bug regarding fitting :class:`cluster.KMeans` with a sparse
+ array X and initial centroids, where X's means were unnecessarily being
+ subtracted from the centroids. :issue:`7872` by :user:`Josh Karnofsky <jkarno>`.
+
+ - Fixes to the input validation in :class:`covariance.EllipticEnvelope`.
+ :issue:`8086` by `Andreas Müller`_.
+
+ - Fixed a bug in :class:`covariance.MinCovDet` where inputting data
+ that produced a singular covariance matrix would cause the helper method
+ ``_c_step`` to throw an exception.
+ :issue:`3367` by :user:`Jeremy Steward <ThatGeoGuy>`
+
+ - Fixed a bug in :class:`manifold.TSNE` affecting convergence of the
+ gradient descent. :issue:`8768` by :user:`David DeTomaso <deto>`.
+
+ - Fixed a bug in :class:`manifold.TSNE` where it stored the incorrect
+ ``kl_divergence_``. :issue:`6507` by :user:`Sebastian Saeger <ssaeger>`.
+
+ - Fixed improper scaling in :class:`cross_decomposition.PLSRegression`
+ with ``scale=True``. :issue:`7819` by :user:`jayzed82 <jayzed82>`.
+
+ - :class:`cluster.bicluster.SpectralCoclustering` and
+ :class:`cluster.bicluster.SpectralBiclustering` ``fit`` method conforms
+ with API by accepting ``y`` and returning the object. :issue:`6126`,
+ :issue:`7814` by :user:`Laurent Direr <ldirer>` and :user:`Maniteja
+ Nandana <maniteja123>`.
+
+ - Fix bug where :mod:`mixture` ``sample`` methods did not return as many
+ samples as requested. :issue:`7702` by :user:`Levi John Wolf <ljwolf>`.
+
+Preprocessing and feature selection
+
+ - For sparse matrices, :func:`preprocessing.normalize` with ``return_norm=True``
+ will now raise a ``NotImplementedError`` with 'l1' or 'l2' norm and with
+ norm 'max' the norms returned will be the same as for dense matrices.
+ :issue:`7771` by `Ang Lu <https://github.com/luang008>`_.
+
+ - Fix a bug where :class:`feature_selection.SelectFdr` did not
+ exactly implement Benjamini-Hochberg procedure. It formerly may have
+ selected fewer features than it should.
+ :issue:`7490` by :user:`Peng Meng <mpjlu>`.
+
+ - Fixed a bug where :class:`linear_model.RandomizedLasso` and
+ :class:`linear_model.RandomizedLogisticRegression` breaks for
+ sparse input. :issue:`8259` by :user:`Aman Dalmia <dalmia>`.
+
+ - Fix a bug where :class:`feature_extraction.FeatureHasher`
+ mandatorily applied a sparse random projection to the hashed features,
+ preventing the use of
+ :class:`feature_extraction.text.HashingVectorizer` in a
+ pipeline with :class:`feature_extraction.text.TfidfTransformer`.
+ :issue:`7565` by :user:`Roman Yurchak <rth>`.
+
+ - Fix a bug where :class:`feature_selection.mutual_info_regression` did not
+ correctly use ``n_neighbors``. :issue:`8181` by :user:`Guillaume Lemaitre
+ <glemaitre>`.
+
+Model evaluation and meta-estimators
+
+ - Fixed a bug where :func:`model_selection.BaseSearchCV.inverse_transform`
+ returns ``self.best_estimator_.transform()`` instead of
+ ``self.best_estimator_.inverse_transform()``.
+ :issue:`8344` by :user:`Akshay Gupta <Akshay0724>` and :user:`Rasmus Eriksson <MrMjauh>`.
+
+ - Added ``classes_`` attribute to :class:`model_selection.GridSearchCV`,
+ :class:`model_selection.RandomizedSearchCV`, :class:`grid_search.GridSearchCV`,
+ and :class:`grid_search.RandomizedSearchCV` that matches the ``classes_``
+ attribute of ``best_estimator_``. :issue:`7661` and :issue:`8295`
+ by :user:`Alyssa Batula <abatula>`, :user:`Dylan Werner-Meier <unautre>`,
+ and :user:`Stephen Hoover <stephen-hoover>`.
+
+ - Fixed a bug where :func:`model_selection.validation_curve`
+ reused the same estimator for each parameter value.
+ :issue:`7365` by :user:`Aleksandr Sandrovskii <Sundrique>`.
+
+ - :func:`model_selection.permutation_test_score` now works with Pandas
+ types. :issue:`5697` by :user:`Stijn Tonk <equialgo>`.
+
- Several fixes to input validation in
:class:`multiclass.OutputCodeClassifier`
:issue:`8086` by `Andreas Müller`_.
- - Fix a bug where
- :class:`ensemble.gradient_boosting.QuantileLossFunction` computed
- negative errors for negative values of ``ytrue - ypred`` leading to
- wrong values when calling ``__call__``.
- :issue:`8087` by :user:`Alexis Mignon <AlexisMignon>`
+ - :class:`multiclass.OneVsOneClassifier`'s ``partial_fit`` now ensures all
+ classes are provided up-front. :issue:`6250` by
+ :user:`Asish Panda <kaichogami>`.
- - Fix :func:`multioutput.MultiOutputClassifier.predict_proba` to
- return a list of 2d arrays, rather than a 3d array. In the case where
- different target columns had different numbers of classes, a `ValueError`
- would be raised on trying to stack matrices with different dimensions.
+ - Fix :func:`multioutput.MultiOutputClassifier.predict_proba` to return a
+ list of 2d arrays, rather than a 3d array. In the case where different
+ target columns had different numbers of classes, a ``ValueError`` would be
+ raised on trying to stack matrices with different dimensions.
:issue:`8093` by :user:`Peter Bull <pjbull>`.
- - Fix a bug where :func:`linear_model.LassoLars.fit` sometimes
- left `coef_` as a list, rather than an ndarray.
- :issue:`8160` by :user:`CJ Carey <perimosocordiae>`.
-
- - Fix a bug where :class:`feature_extraction.FeatureHasher`
- mandatorily applied a sparse random projection to the hashed features,
- preventing the use of
- :class:`feature_extraction.text.HashingVectorizer` in a
- pipeline with :class:`feature_extraction.text.TfidfTransformer`.
- :issue:`7513` by :user:`Roman Yurchak <rth>`.
-
- - Fix a bug in cases where ``numpy.cumsum`` may be numerically unstable,
- raising an exception if instability is identified. :issue:`7376` and
- :issue:`7331` by `Joel Nothman`_ and :user:`yangarbiter`.
+Metrics
- - Fix a bug where :meth:`base.BaseEstimator.__getstate__`
- obstructed pickling customizations of child-classes, when used in a
- multiple inheritance context.
- :issue:`8316` by :user:`Holger Peters <HolgerPeters>`.
+ - :func:`metrics.average_precision_score` no longer linearly
+ interpolates between operating points, and instead weighs precisions
+ by the change in recall since the last operating point, as per the
+ `Wikipedia entry <http://en.wikipedia.org/wiki/Average_precision>`_.
+ (`#7356 <https://github.com/scikit-learn/scikit-learn/pull/7356>`_). By
+ :user:`Nick Dingwall <ndingwall>` and `Gael Varoquaux`_.
- Fix a bug in :func:`metrics.classification._check_targets`
which would return ``'binary'`` if ``y_true`` and ``y_pred`` were
both ``'binary'`` but the union of ``y_true`` and ``y_pred`` was
``'multiclass'``. :issue:`8377` by `Loic Esteve`_.
+ - Fixed an integer overflow bug in :func:`metrics.confusion_matrix` and
+ hence :func:`metrics.cohen_kappa_score`. :issue:`8354`, :issue:`7929`
+ by `Joel Nothman`_ and :user:`Jon Crall <Erotemic>`.
- - Fix :func:`linear_model.BayesianRidge.fit` to return
- ridge parameter `alpha_` and `lambda_` consistent with calculated
- coefficients `coef_` and `intercept_`.
- :issue:`8224` by :user:`Peter Gedeck <gedeck>`.
-
- - Fixed a bug in :class:`manifold.TSNE` where it stored the incorrect
- ``kl_divergence_``. :issue:`6507` by :user:`Sebastian Saeger <ssaeger>`.
-
- - Fixed a bug in :class:`svm.OneClassSVM` where it returned floats instead of
- integer classes. :issue:`8676` by :user:`Vathsala Achar <VathsalaAchar>`.
+ - Fixed passing of ``gamma`` parameter to the ``chi2`` kernel in
+ :func:`metrics.pairwise.pairwise_kernels` :issue:`5211` by
+ :user:`Nick Rhinehart <nrhine1>`,
+ :user:`Saurabh Bansod <mth4saurabh>` and `Andreas Müller`_.
- - Fixed a bug where :func:`tree.export_graphviz` raised an error
- when the length of features_names does not match n_features in the decision
- tree. :issue:`8512` by :user:`Li Li <aikinogard>`.
+Miscellaneous
- - Fixed a bug in :class:`manifold.TSNE` affecting convergence of the
- gradient descent. :issue:`8768` by :user:`David DeTomaso <deto>`.
+ - Fixed a bug when :func:`datasets.make_classification` fails
+ when generating more than 30 features. :issue:`8159` by
+ :user:`Herilalaina Rakotoarison <herilalaina>`.
- - Fixed a memory leak in our LibLinear implementation. :issue:`9024` by
- :user:`Sergei Lebedev <superbobry>`
- - Fixed improper scaling in :class:`cross_decomposition.PLSRegression`
- with ``scale=True``. :issue:`7819` by :user:`jayzed82 <jayzed82>`.
+ - Fixed a bug where :func:`datasets.make_moons` gives an
+ incorrect result when ``n_samples`` is odd.
+ :issue:`8198` by :user:`Josh Levy <levy5674>`.
- - Fixed oob_score in :class:`ensemble.BaggingClassifier`.
- :issue:`8936` by :user:`mlewis1729 <mlewis1729>`
+ - Some ``fetch_`` functions in :mod:`datasets` were ignoring the
+ ``download_if_missing`` keyword. :issue:`7944` by :user:`Ralf Gommers <rgommers>`.
- - Add ``shuffle`` parameter to :func:`model_selection.train_test_split`.
- :issue:`8845` by :user:`themrmax <themrmax>`
+ - Fix estimators to accept a ``sample_weight`` parameter of type
+ ``pandas.Series`` in their ``fit`` function. :issue:`7825` by
+ `Kathleen Chen`_.
- - Fix AIC/BIC criterion computation in :class:`linear_model.LassoLarsIC`.
- :issue:`9022` by `Alexandre Gramfort`_ and :user:`Mehmet Basbug <mehmetbasbug>`.
+ - Fix a bug in cases where ``numpy.cumsum`` may be numerically unstable,
+ raising an exception if instability is identified. :issue:`7376` and
+ :issue:`7331` by `Joel Nothman`_ and :user:`yangarbiter`.
- - Fix bug where stratified CV splitters did not work with
- :class:`linear_model.LassoCV`. :issue:`8973` by
- :user:`Paulo Haddad <paulochf>`.
+ - Fix a bug where :meth:`base.BaseEstimator.__getstate__`
+ obstructed pickling customizations of child-classes, when used in a
+ multiple inheritance context.
+ :issue:`8316` by :user:`Holger Peters <HolgerPeters>`.
- - Fixed a bug in :class:`linear_model.RandomizedLasso`,
- :class:`linear_model.Lars`, :class:`linear_model.LassoLars`,
- :class:`linear_model.LarsCV` and :class:`linear_model.LassoLarsCV`,
- where the parameter ``precompute`` were not used consistently across
- classes, and some values proposed in the docstring could raise errors.
- :issue:`5359` by `Tom Dupre la Tour`_.
+ - Update Sphinx-Gallery from 0.1.4 to 0.1.7 for resolving links in
+ documentation build with Sphinx>1.5 :issue:`8010`, :issue:`7986` by
+ :user:`Oscar Najera <Titan-C>`
- - Fixed a bug where :func:`model_selection.validation_curve`
- reused the same estimator for each parameter value.
- :issue:`7365` by :user:`Aleksandr Sandrovskii <Sundrique>`.
+ - Add ``data_home`` parameter to :func:`sklearn.datasets.fetch_kddcup99`.
+ :issue:`9289` by `Loic Esteve`_.
- - :class:`multiclass.OneVsOneClassifier`'s ``partial_fit`` now ensures all
- classes are provided up-front. :issue:`6250` by
- :user:`Asish Panda <kaichogami>`.
+ - Fix dataset loaders using Python 3 version of makedirs to also work in
+ Python 2. :issue:`9284` by :user:`Sebastin Santy <SebastinSanty>`.
- - Fixed an integer overflow bug in :func:`metrics.confusion_matrix` and
- hence :func:`metrics.cohen_kappa_score`. :issue:`8354`, :issue:`7929`
- by `Joel Nothman`_ and :user:`Jon Crall <Erotemic>`.
+ - Several minor issues were fixed with thanks to the alerts of
+ [lgtm.com](http://lgtm.com). :issue:`9278` by :user:`Jean Helie <jhelie>`,
+ among others.
- - Made default kernel parameters kernel-dependent in :class:`kernel_approximation.Nystroem`
- :issue:`5229` by :user:`mth4saurabh` and `Andreas Müller`_.
+API changes summary
+-------------------
- - Fixed passing of ``gamma`` parameter to the ``chi2`` kernel in
- :func:`metrics.pairwise_kernels` :issue:`5211` by :user:`nrhine1`,
- :user:`mth4saurabh` and `Andreas Müller`_.
+Trees and ensembles
- - Fixed a bug in :class:`gaussian_process.GaussianProcessRegressor`
- when the standard deviation and covariance predicted without fit
- would fail with a unmeaningful error by default.
- :issue:`6573` by :user:`Quazi Marufur Rahman <qmaruf>` and
- `Manoj Kumar`_.
+ - Gradient boosting base models are no longer estimators. By `Andreas Müller`_.
- - Fixed the implementation of `explained_variance_`
- in :class:`decomposition.PCA`,
- :class:`decomposition.RandomizedPCA` and
- :class:`decomposition.IncrementalPCA`.
- :issue:`9105` by `Hanmin Qin <https://github.com/qinhanmin2014>`_.
+ - All tree based estimators now accept a ``min_impurity_decrease``
+ parameter in lieu of the ``min_impurity_split``, which is now deprecated.
+ The ``min_impurity_decrease`` helps stop splitting the nodes in which
+ the weighted impurity decrease from splitting is no longer alteast
+ ``min_impurity_decrease``. :issue:`8449` by `Raghav RV`_.
- - Fix :class:`semi_supervised.BaseLabelPropagation` to correctly implement
- ``LabelPropagation`` and ``LabelSpreading`` as done in the referenced
- papers. :class:`semi_supervised.LabelPropagation` now always does hard
- clamping. Its ``alpha`` parameter has no effect and is
- deprecated to be removed in 0.21. :issue:`6727` :issue:`3550` issue:`5770`
- by :user:`Andre Ambrosio Boechat <boechat107>`, :user:`Utkarsh Upadhyay
- <musically-ut>`, and `Joel Nothman`_.
+Linear, kernelized and related models
- - Add ``data_home`` parameter to
- :func:`sklearn.datasets.fetch_kddcup99` by `Loic Esteve`_.
+ - ``n_iter`` parameter is deprecated in :class:`linear_model.SGDClassifier`,
+ :class:`linear_model.SGDRegressor`,
+ :class:`linear_model.PassiveAggressiveClassifier`,
+ :class:`linear_model.PassiveAggressiveRegressor` and
+ :class:`linear_model.Perceptron`. By `Tom Dupre la Tour`_.
- - Fix inconsistent results between :class:`linear_model.RidgeCV`
- and :class:`linear_model.Ridge` when using ``normalize=True``
- by `Alexandre Gramfort`_.
+Other predictors
- - Fixed the implementation of :class:`manifold.TSNE`:
- - ``early_exageration`` parameter had no effect and is now used for the
- first 250 optimization iterations.
- - Fixed the ``InsersionError`` reported in :issue:`8992`.
- - Improve the learning schedule to match the one from the reference
- implementation `lvdmaaten/bhtsne <https://github.com/lvdmaaten/bhtsne>`_.
- by :user:`Thomas Moreau <tomMoral>` and `Olivier Grisel`_.
+ - :class:`neighbors.LSHForest` has been deprecated and will be
+ removed in 0.21 due to poor performance.
+ :issue:`9078` by :user:`Laurent Direr <ldirer>`.
-API changes summary
--------------------
+ - :class:`neighbors.NearestCentroid` no longer purports to support
+ ``metric='precomputed'`` which now raises an error. :issue:`8515` by
+ :user:`Sergul Aydore <sergulaydore>`.
- - Ensure that estimators' attributes ending with ``_`` are not set
- in the constructor but only in the ``fit`` method. Most notably,
- ensemble estimators (deriving from :class:`ensemble.BaseEnsemble`)
- now only have ``self.estimators_`` available after ``fit``.
- :issue:`7464` by `Lars Buitinck`_ and `Loic Esteve`_.
+ - The ``alpha`` parameter of :class:`semi_supervised.LabelPropagation` now
+ has no effect and is deprecated to be removed in 0.21. :issue:`9239`
+ by :user:`Andre Ambrosio Boechat <boechat107>`, :user:`Utkarsh Upadhyay
+ <musically-ut>`, and `Joel Nothman`_.
- - All checks in ``utils.estimator_checks``, in particular
- :func:`utils.estimator_checks.check_estimator` now accept estimator
- instances. Most other checks do not accept
- estimator classes any more. :issue:`9019` by `Andreas Müller`_.
+Decomposition, manifold learning and clustering
- Deprecate the ``doc_topic_distr`` argument of the ``perplexity`` method
in :class:`decomposition.LatentDirichletAllocation` because the
@@ -515,20 +694,38 @@ API changes summary
needed for the perplexity calculation. :issue:`7954` by
:user:`Gary Foreman <garyForeman>`.
- - Replace attribute ``named_steps`` ``dict`` to :class:`utils.Bunch`
- in :class:`pipeline.Pipeline` to enable tab completion in interactive
- environment. In the case conflict value on ``named_steps`` and ``dict``
- attribute, ``dict`` behavior will be prioritized.
- :issue:`8481` by :user:`Herilalaina Rakotoarison <herilalaina>`.
+ - The ``n_topics`` parameter of :class:`decomposition.LatentDirichletAllocation`
+ has been renamed to ``n_components`` and will be removed in version 0.21.
+ :issue:`8922` by :user:`Attractadore`.
- - The :func:`multioutput.MultiOutputClassifier.predict_proba`
- function used to return a 3d array (``n_samples``, ``n_classes``,
- ``n_outputs``). In the case where different target columns had different
- numbers of classes, a `ValueError` would be raised on trying to stack
- matrices with different dimensions. This function now returns a list of
- arrays where the length of the list is ``n_outputs``, and each array is
- (``n_samples``, ``n_classes``) for that particular output.
- :issue:`8093` by :user:`Peter Bull <pjbull>`.
+ - :meth:`decomposition.SparsePCA.transform`'s ``ridge_alpha`` parameter is
+ deprecated in preference for class parameter.
+ :issue:`8137` by :user:`Naoya Kanai <naoyak>`.
+
+ - :class:`cluster.DBSCAN` now has a ``metric_params`` parameter.
+ :issue:`8139` by :user:`Naoya Kanai <naoyak>`.
+
+Preprocessing and feature selection
+
+ - :class:`feature_selection.SelectFromModel` now has a ``partial_fit``
+ method only if the underlying estimator does. By `Andreas Müller`_.
+
+ - :class:`feature_selection.SelectFromModel` now validates the ``threshold``
+ parameter and sets the ``threshold_`` attribute during the call to
+ ``fit``, and no longer during the call to ``transform```. By `Andreas
+ Müller`_.
+
+ - The ``non_negative`` parameter in :class:`feature_extraction.FeatureHasher`
+ has been deprecated, and replaced with a more principled alternative,
+ ``alternate_sign``.
+ :issue:`7565` by :user:`Roman Yurchak <rth>`.
+
+ - :class:`linear_model.RandomizedLogisticRegression`,
+ and :class:`linear_model.RandomizedLasso` have been deprecated and will
+ be removed in version 0.21.
+ :issue:`8995` by :user:`Ramana.S <sentient07>`.
+
+Model evaluation and meta-estimators
- Deprecate the ``fit_params`` constructor input to the
:class:`model_selection.GridSearchCV` and
@@ -541,56 +738,49 @@ API changes summary
:func:`model_selection.cross_val_predict`.
:issue:`2879` by :user:`Stephen Hoover <stephen-hoover>`.
- - The ``decision_function`` output shape for binary classification in
- :class:`multiclass.OneVsRestClassifier` and
- :class:`multiclass.OneVsOneClassifier` is now ``(n_samples,)`` to conform
- to scikit-learn conventions. :issue:`9100` by `Andreas Müller`_.
-
- - Gradient boosting base models are no longer estimators. By `Andreas Müller`_.
-
- - :class:`feature_selection.SelectFromModel` now validates the ``threshold``
- parameter and sets the ``threshold_`` attribute during the call to
- ``fit``, and no longer during the call to ``transform```, by `Andreas
- Müller`_.
+ - In version 0.21, the default behavior of splitters that use the
+ ``test_size`` and ``train_size`` parameter will change, such that
+ specifying ``train_size`` alone will cause ``test_size`` to be the
+ remainder. :issue:`7459` by :user:`Nelson Liu <nelson-liu>`.
- - :class:`feature_selection.SelectFromModel` now has a ``partial_fit``
- method only if the underlying estimator does. By `Andreas Müller`_.
+ - :class:`multiclass.OneVsRestClassifier` now has ``partial_fit``,
+ ``decision_function`` and ``predict_proba`` methods only when the
+ underlying estimator does. :issue:`7812` by `Andreas Müller`_ and
+ :user:`Mikhail Korobov <kmike>`.
- :class:`multiclass.OneVsRestClassifier` now has a ``partial_fit`` method
only if the underlying estimator does. By `Andreas Müller`_.
- - Estimators with both methods ``decision_function`` and ``predict_proba``
- are now required to have a monotonic relation between them. The
- method ``check_decision_proba_consistency`` has been added in
- **sklearn.utils.estimator_checks** to check their consistency.
- :issue:`7578` by :user:`Shubham Bhardwaj <shubham0704>`
-
- - In version 0.21, the default behavior of splitters that use the
- ``test_size`` and ``train_size`` parameter will change, such that
- specifying ``train_size`` alone will cause ``test_size`` to be the
- remainder. :issue:`7459` by :user:`Nelson Liu <nelson-liu>`.
+ - The ``decision_function`` output shape for binary classification in
+ :class:`multiclass.OneVsRestClassifier` and
+ :class:`multiclass.OneVsOneClassifier` is now ``(n_samples,)`` to conform
+ to scikit-learn conventions. :issue:`9100` by `Andreas Müller`_.
- - All tree based estimators now accept a ``min_impurity_decrease``
- parameter in lieu of the ``min_impurity_split``, which is now deprecated.
- The ``min_impurity_decrease`` helps stop splitting the nodes in which
- the weighted impurity decrease from splitting is no longer alteast
- ``min_impurity_decrease``. :issue:`8449` by `Raghav RV`_.
+ - The :func:`multioutput.MultiOutputClassifier.predict_proba`
+ function used to return a 3d array (``n_samples``, ``n_classes``,
+ ``n_outputs``). In the case where different target columns had different
+ numbers of classes, a ``ValueError`` would be raised on trying to stack
+ matrices with different dimensions. This function now returns a list of
+ arrays where the length of the list is ``n_outputs``, and each array is
+ (``n_samples``, ``n_classes``) for that particular output.
+ :issue:`8093` by :user:`Peter Bull <pjbull>`.
- - The ``n_topics`` parameter of :class:`decomposition.LatentDirichletAllocation`
- has been renamed to ``n_components`` and will be removed in version 0.21.
- :issue:`8922` by :user:`Attractadore`
+ - Replace attribute ``named_steps`` ``dict`` to :class:`utils.Bunch`
+ in :class:`pipeline.Pipeline` to enable tab completion in interactive
+ environment. In the case conflict value on ``named_steps`` and ``dict``
+ attribute, ``dict`` behavior will be prioritized.
+ :issue:`8481` by :user:`Herilalaina Rakotoarison <herilalaina>`.
- - :class:`cluster.bicluster.SpectralCoclustering` and
- :class:`cluster.bicluster.SpectralBiclustering` now accept ``y`` in fit.
- :issue:`6126` by :user:ldirer
+Miscellaneous
- - :class:`neighbors.LSHForest` has been deprecated and will be
- removed in 0.21 due to poor performance.
- :issue:`8996` by `Andreas Müller`_.
+ - Deprecate the ``y`` parameter in ``transform`` and ``inverse_transform``.
+ The method should not accept ``y`` parameter, as it's used at the prediction time.
+ :issue:`8174` by :user:`Tahar Zanouda <tzano>`, `Alexandre Gramfort`_
+ and `Raghav RV`_.
- SciPy >= 0.13.3 and NumPy >= 1.8.2 are now the minimum supported versions
for scikit-learn. The following backported functions in
- :mod:`sklearn.utils` have been removed or deprecated accordingly.
+ :mod:`utils` have been removed or deprecated accordingly.
:issue:`8854` and :issue:`8874` by :user:`Naoya Kanai <naoyak>`
Removed in 0.19:
@@ -619,21 +809,31 @@ API changes summary
- ``utils.random.choice``
- ``utils.sparsetools.connected_components``
- ``utils.stats.rankdata``
- - ``neighbors.approximate.LSHForest``
- - ``linear_model.randomized_l1``
- - Deprecate the ``y`` parameter in `transform` and `inverse_transform`.
- The method should not accept ``y`` parameter, as it's used at the prediction time.
- :issue:`8174` by :user:`Tahar Zanouda <tzano>`, `Alexandre Gramfort`_
- and `Raghav RV`_.
+ - Estimators with both methods ``decision_function`` and ``predict_proba``
+ are now required to have a monotonic relation between them. The
+ method ``check_decision_proba_consistency`` has been added in
+ **utils.estimator_checks** to check their consistency.
+ :issue:`7578` by :user:`Shubham Bhardwaj <shubham0704>`
+
+ - All checks in ``utils.estimator_checks``, in particular
+ :func:`utils.estimator_checks.check_estimator` now accept estimator
+ instances. Most other checks do not accept
+ estimator classes any more. :issue:`9019` by `Andreas Müller`_.
+
+ - Ensure that estimators' attributes ending with ``_`` are not set
+ in the constructor but only in the ``fit`` method. Most notably,
+ ensemble estimators (deriving from :class:`ensemble.BaseEnsemble`)
+ now only have ``self.estimators_`` available after ``fit``.
+ :issue:`7464` by `Lars Buitinck`_ and `Loic Esteve`_.
-.. _changes_0_18_1:
+.. _changes_0_18_2:
-Version 0.18.1
+Version 0.18.2
==============
-**November 11, 2016**
+**June 20, 2017**
.. topic:: Last release with Python 2.6 support
@@ -641,6 +841,27 @@ Version 0.18.1
Later versions of scikit-learn will require Python 2.7 or above.
+Changelog
+---------
+
+ - Fixes for compatibility with NumPy 1.13.0: :issue:`7946` :issue:`8355` by
+ `Loic Esteve`_.
+
+ - Minor compatibility changes in the examples :issue:`9010` :issue:`8040`
+ :issue:`9149`.
+
+Code Contributors
+-----------------
+Aman Dalmia, Loic Esteve, Nate Guerin, Sergei Lebedev
+
+
+.. _changes_0_18_1:
+
+Version 0.18.1
+==============
+
+**November 11, 2016**
+
Changelog
---------
@@ -741,6 +962,13 @@ Bug fixes
parameter setting on the split produced by the first ``split`` call
to the cross-validation splitter. :issue:`7660` by `Raghav RV`_.
+ - Fix bug where :meth:`preprocessing.MultiLabelBinarizer.fit_transform`
+ returned an invalid CSR matrix.
+ :issue:`7750` by :user:`CJ Carey <perimosocordiae>`.
+
+ - Fixed a bug where :func:`metrics.pairwise.cosine_distances` could return a
+ small negative distance. :issue:`7732` by :user:`Artsion <asanakoy>`.
+
API changes summary
-------------------
@@ -1352,8 +1580,10 @@ Model evaluation and meta-estimators
the parameter ``n_labels`` is renamed to ``n_groups``.
:issue:`6660` by `Raghav RV`_.
- - The :mod:`sklearn.linear_model.randomized_l1` is deprecated.
- :issue: `8995` by :user:`Ramana.S <sentient07>`.
+ - Error and loss names for ``scoring`` parameters are now prefixed by
+ ``'neg_'``, such as ``neg_mean_squared_error``. The unprefixed versions
+ are deprecated and will be removed in version 0.20.
+ :issue:`7261` by :user:`Tim Head <betatim>`.
Code Contributors
-----------------