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DOC fix various syntax in whats_new (scikit-learn#7421)
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@TomDLT @amueller
TomDLT authored and amueller committed Sep 14, 2016
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Expand Up @@ -19,9 +19,10 @@ Model Selection Enhancements and API Changes
- **The ``model_selection`` module**

The new module :mod:`sklearn.model_selection`, which groups together the
functionalities of formerly :mod:`cross_validation`, :mod:`grid_search` and
:mod:`learning_curve`, introduces new possibilities such as nested
cross-validation and better manipulation of parameter searches with Pandas.
functionalities of formerly :mod:`sklearn.cross_validation`,
:mod:`sklearn.grid_search` and :mod:`sklearn.learning_curve`, introduces new
possibilities such as nested cross-validation and better manipulation of
parameter searches with Pandas.

Many things will stay the same but there are some key differences. Read
below to know more about the changes.
Expand Down Expand Up @@ -245,7 +246,7 @@ Enhancements
- Prediction of out-of-sample events with Isotonic Regression is now much
faster (over 1000x in tests with synthetic data). By `Jonathan Arfa`_.

- Added ``inverse_transform`` function to :class:`decomposition.nmf` to compute
- Added ``inverse_transform`` function to :class:`decomposition.NMF` to compute
data matrix of original shape. By `Anish Shah`_.

- :class:`naive_bayes.GaussianNB` now accepts data-independent class-priors
Expand All @@ -254,8 +255,10 @@ Enhancements
- Add option to show ``indicator features`` in the output of Imputer.
By `Mani Teja`_.

- Reduce the memory usage for 32-bit float input arrays of :func:`utils.mean_variance_axis` and
:func:`utils.incr_mean_variance_axis` by supporting cython fused types. By `YenChen Lin`_.
- Reduce the memory usage for 32-bit float input arrays of
:func:`utils.sparse_func.mean_variance_axis` and
:func:`utils.sparse_func.incr_mean_variance_axis` by supporting cython
fused types. By `YenChen Lin`_.

- The :func: `ignore_warnings` now accept a category argument to ignore only
the warnings of a specified type. By `Thierry Guillemot`_.
Expand Down Expand Up @@ -285,15 +288,16 @@ Enhancements
`#7154 <https://github.com/scikit-learn/scikit-learn/pull/7154>`_ by
`Manvendra Singh`_.

- :class:`RobustScaler` now accepts ``quantile_range`` parameter.
- :class:`preprocessing.RobustScaler` now accepts ``quantile_range`` parameter.
(`#5929 <https://github.com/scikit-learn/scikit-learn/pull/5929>`_)
By `Konstantin Podshumok`_.

- The memory footprint is reduced (sometimes greatly) for :class:`BaseBagging`
and classes that inherit from it, i.e, :class:`BaggingClassifier`,
:class:`BaggingRegressor`, and :class:`IsolationForest`, by dynamically
generating attribute ``estimators_samples_`` only when it is needed.
By `David Staub`_.
- The memory footprint is reduced (sometimes greatly) for
:class:`ensemble.bagging.BaseBagging` and classes that inherit from it,
i.e, :class:`ensemble.BaggingClassifier`,
:class:`ensemble.BaggingRegressor`, and :class:`ensemble.IsolationForest`,
by dynamically generating attribute ``estimators_samples_`` only when it is
needed. By `David Staub`_.

- :class:`linear_model.ElasticNet` and :class:`linear_model.Lasso`
now works with ``np.float32`` input data without converting it
Expand All @@ -307,8 +311,8 @@ Enhancements
(`#7239 <https://github.com/scikit-learn/scikit-learn/pull/7239/>`_)
by `Hong Guangguo`_ with help from `Mads Jensen`_ and `Nelson Liu`_.

- Added ``n_jobs`` and ``sample_weights`` parameters for :class:`VotingClassifier`
to fit underlying estimators in parallel.
- Added ``n_jobs`` and ``sample_weights`` parameters for
:class:`ensemble.VotingClassifier` to fit underlying estimators in parallel.
(`#5805 <https://github.com/scikit-learn/scikit-learn/pull/5805>`_)
By `Ibraim Ganiev`_.

Expand All @@ -320,28 +324,29 @@ Enhancements

- Simplification of the ``clone`` function, deprecate support for estimators
that modify parameters in ``__init__``.
(`#5540 <https://github.com/scikit-learn/scikit-learn/pull/5540>_`)
(`#5540 <https://github.com/scikit-learn/scikit-learn/pull/5540>`_)
By `Andreas Müller`_.

- When unpickling a scikit-learn estimator in a different version than the one
the estimator was trained with, a ``UserWarning`` is raised, see :ref:`the documentation
on model persistence <persistence_limitations>`
for more details.
(`#7248 <https://github.com/scikit-learn/scikit-learn/pull/7248>_`)
(`#7248 <https://github.com/scikit-learn/scikit-learn/pull/7248>`_)
By `Andreas Müller`_.

Bug fixes
.........

- :func: `model_selection.tests._search._check_param_grid` now works correctly with all types
- :func:`model_selection.tests._search._check_param_grid` now works correctly with all types
that extends/implements `Sequence` (except string), including range (Python 3.x) and xrange
(Python 2.x).
(`#7323 <https://github.com/scikit-learn/scikit-learn/pull/7323>`_) by `Viacheslav Kovalevskyi`_.

- :class:`StratifiedKFold` now raises error if all n_labels for individual classes is less than n_folds.
- :class:`model_selection.StratifiedKFold` now raises error if all n_labels
for individual classes is less than n_folds.
(`#6182 <https://github.com/scikit-learn/scikit-learn/pull/6182>`_) by `Devashish Deshpande`_.

- :class:`RandomizedPCA` default number of `iterated_power` is 4 instead of 3.
- :class:`decomposition.RandomizedPCA` default number of `iterated_power` is 4 instead of 3.
(`#5141 <https://github.com/scikit-learn/scikit-learn/pull/5141>`_) by `Giorgio Patrini`_.

- :func:`utils.extmath.randomized_svd` performs 4 power iterations by default, instead or 0.
Expand All @@ -366,15 +371,15 @@ Bug fixes
Laplacian matrix was incorrectly set to 1. (`#4995 <https://github.com/scikit-learn/scikit-learn/pull/4995>`_) By `Peter Fischer`_.

- Fixed incorrect initialization of :func:`utils.arpack.eigsh` on all
occurrences. Affects :class:`cluster.SpectralBiclustering`,
occurrences. Affects :class:`cluster.bicluster.SpectralBiclustering`,
:class:`decomposition.KernelPCA`, :class:`manifold.LocallyLinearEmbedding`,
and :class:`manifold.SpectralEmbedding` (`#5012 <https://github.com/scikit-learn/scikit-learn/pull/5012>`_). By `Peter Fischer`_.

- Random forest, extra trees, decision trees and gradient boosting
won't accept anymore ``min_samples_split=1`` as at least 2 samples
are required to split a decision tree node. By `Arnaud Joly`_

- :class:`VotingClassifier` now raises ``NotFittedError`` if ``predict``,
- :class:`ensemble.VotingClassifier` now raises ``NotFittedError`` if ``predict``,
``transform`` or ``predict_proba`` are called on the non-fitted estimator.
by `Sebastian Raschka`_.

Expand Down Expand Up @@ -409,20 +414,20 @@ Bug fixes
<https://github.com/scikit-learn/scikit-learn/issues/6902>`_). By
`LeonieBorne <https://github.com/LeonieBorne>`_.

- :func:`pairwise_distances` now converts arrays to boolean arrays when
required in scipy.spatial.distance.
- :func:`metrics.pairwise.pairwise_distances` now converts arrays to
boolean arrays when required in scipy.spatial.distance.
(`#5460 <https://github.com/scikit-learn/scikit-learn/pull/5460>`_)
By `Tom Dupre la Tour`_.

- :func:`datasets.load_svmlight_file` now is able to read long int QID values.
(`#7101 <https://github.com/scikit-learn/scikit-learn/pull/7101>`_)
By `Ibraim Ganiev`_.

- Fix sparse input support in :func:`silhouette_score` as well as example
examples/text/document_clustering.py. By `YenChen Lin`_.
- Fix sparse input support in :func:`metrics.silhouette_score` as well as
example examples/text/document_clustering.py. By `YenChen Lin`_.

- :func:`_transform_selected` now always passes a copy of `X` to transform
function when `copy=True` (`#7194
- :func:`preprocessing.data._transform_selected` now always passes a copy
of `X` to transform function when `copy=True` (`#7194
<https://github.com/scikit-learn/scikit-learn/issues/7194>`_). By `Caio
Oliveira <https://github.com/caioaao>`_.

Expand All @@ -431,7 +436,7 @@ Bug fixes

- Fix in :class:`sklearn.model_selection.StratifiedShuffleSplit` to
return splits of size ``train_size`` and ``test_size`` in all cases
(`#6472 <https://github.com/scikit-learn/scikit-learn/pull/6472>`).
(`#6472 <https://github.com/scikit-learn/scikit-learn/pull/6472>`_).
By `Andreas Müller`_.

- :func:`metrics.roc_curve` and :func:`metrics.precision_recall_curve` no
Expand All @@ -451,8 +456,8 @@ API changes summary

- The :mod:`sklearn.cross_validation`, :mod:`sklearn.grid_search` and
:mod:`sklearn.learning_curve` have been deprecated and the classes and
functions have been reorganized into the :mod:`model_selection` module.
Ref :ref:`model_selection_changes` for more information.
functions have been reorganized into the :mod:`sklearn.model_selection`
module. Ref :ref:`model_selection_changes` for more information.
(`#4294 <https://github.com/scikit-learn/scikit-learn/pull/4294>`_) by
`Raghav R V`_.

Expand All @@ -462,26 +467,26 @@ API changes summary
- Access to public attributes ``.X_`` and ``.y_`` has been deprecated in
:class:`isotonic.IsotonicRegression`. By `Jonathan Arfa`_.

- The old :class:`VBGMM` is deprecated in favor of the new
:class:`BayesianGaussianMixture` (with the parameter
``weight_concentration_prior_type='dirichlet_distribution'``).
- The old :class:`mixture.DPGMM` is deprecated in favor of the new
:class:`mixture.BayesianGaussianMixture` (with the parameter
``weight_concentration_prior_type='dirichlet_process'``).
The new class solves the computational
problems of the old class and computes the Gaussian mixture with a
Dirichlet process prior faster than before.
(`#7295 <https://github.com/scikit-learn/scikit-learn/pull/7295>`_) by
`Wei Xue`_ and `Thierry Guillemot`_.

- The old :class:`VBGMM` is deprecated in favor of the new
:class:`BayesianGaussianMixture` (with the parameter
- The old :class:`mixture.VBGMM` is deprecated in favor of the new
:class:`mixture.BayesianGaussianMixture` (with the parameter
``weight_concentration_prior_type='dirichlet_distribution'``).
The new class solves the computational
problems of the old class and computes the Variational Bayesian Gaussian
mixture faster than before.
(`#6651 <https://github.com/scikit-learn/scikit-learn/pull/6651>`_) by
`Wei Xue`_ and `Thierry Guillemot`_.

- The old :class:`GMM` is deprecated in favor of the new
:class:`GaussianMixture`. The new class computes the Gaussian mixture
- The old :class:`mixture.GMM` is deprecated in favor of the new
:class:`mixture.GaussianMixture`. The new class computes the Gaussian mixture
faster than before and some of computational problems have been solved.
(`#6666 <https://github.com/scikit-learn/scikit-learn/pull/6666>`_) by
`Wei Xue`_ and `Thierry Guillemot`_.
Expand All @@ -499,12 +504,12 @@ API changes summary
(`#7187 <https://github.com/scikit-learn/scikit-learn/pull/7187>`_)
by `YenChen Lin`_.

- ``classes`` parameter was renamed to ``labels`` in
:func:`metrics.classification.hamming_loss`.
(`#7260 <https://github.com/scikit-learn/scikit-learn/pull/7260>`_) by
`Sebastián Vanrell`_.
- The splitter classes ``LabelKFold``, ``LabelShuffleSplit``,
- ``classes`` parameter was renamed to ``labels`` in
:func:`metrics.classification.hamming_loss`.
(`#7260 <https://github.com/scikit-learn/scikit-learn/pull/7260>`_) by
`Sebastián Vanrell`_.

- The splitter classes ``LabelKFold``, ``LabelShuffleSplit``,
``LeaveOneLabelOut`` and ``LeavePLabelsOut`` are renamed to
:class:`model_selection.GroupKFold`,
:class:`model_selection.GroupShuffleSplit`,
Expand Down

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