10000 minor fixes to whatsnew · scikit-learn/scikit-learn@f6c1758 · GitHub
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minor fixes to whatsnew
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doc/whats_new.rst

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@@ -110,9 +110,10 @@ Bug fixes
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``download_if_missing`` keyword. This was fixed in :issue:`7944` by
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:user:`Ralf Gommers <rgommers>`.
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- Fix a bug regarding fitting :class:`sklearn.cluster.KMeans` with a
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sparse array X and initial centroids, where X's means were unnecessarily
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being subtracted from the centroids. :issue:`7872` by `Josh Karnofsky <https://github.com/jkarno>`_.
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- Fix a bug regarding fitting :class:`sklearn.cluster.KMeans` with a sparse
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array X and initial centroids, where X's means were unnecessarily being
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subtracted from the centroids. :issue:`7872` by `Josh Karnofsky
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<https://github.com/jkarno>`_.
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- Fix estimators to accept a ``sample_weight`` parameter of type
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``pandas.Series`` in their ``fit`` function. :issue:`7825` by
@@ -126,13 +127,16 @@ Bug fixes
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:class:`sklearn.ensemble.GradientBoostingRegressor` ignored the
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``min_impurity_split`` parameter.
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:issue:`8006` by :user:`Sebastian Pölsterl <sebp>`.
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- Fixes to the input validation in :class:`sklearn.covariance.EllipticEnvelope` by
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`Andreas Müller`_.
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- Fix shape output shape of :class:`sklearn.decomposition.DictionaryLearning` transform
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for one-dimensional data by `Andreas Müller`_.
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- Fixes to the input validation in
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:class:`sklearn.covariance.EllipticEnvelope` by `Andreas Müller`_.
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- Fix shape output shape of
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:class:`sklearn.decomposition.DictionaryLearning` transform for
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one-dimensional data by `Andreas Müller`_.
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- Several fixes to input validation in :class:`multiclass.OutputCodeClassifier` by `Andreas Müller`_
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- Several fixes to input validation in
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:class:`multiclass.OutputCodeClassifier` by `Andreas Müller`_
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API changes summary
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-------------------
@@ -146,29 +150,26 @@ API changes summary
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- Gradient boosting base models are not longer estimators. By `Andreas Müller`_.
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- `feature_extraction.text.TfidfTransformer` now supports numpy arrays as inputs, and produces numpy
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arrays for list inputs and numpy array inputs. By `Andreas `Müller_.
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- :class:`feature_extraction.text.TfidfTransformer` now supports numpy
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arrays as inputs, and produces numpy arrays for list inputs and numpy
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array inputs. By `Andreas `Müller_.
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- `feature_selection.SelectFromModel` now validates the ``threshold``
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- :class:`feature_selection.SelectFromModel` now validates the ``threshold``
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parameter and sets the ``threshold_`` attribute during the call to
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``fit``, and no longer during the call to ``transform```, by `Andreas Müller`_.
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- `features_selection.SelectFromModel` now has a ``partial_fit`` method only if the underlying
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estimator does. By `Andreas Müller`_.
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``fit``, and no longer during the call to ``transform```, by `Andreas
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Müller`_.
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- All checks in ``utils.estimator_checks``, in particular :func:`utils.estimator_checks.check_estimator` now
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accept estimator instances. All checks apart from ``check_estimator`` do not accept estimator classes any more.
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By `Andreas Müller`_.
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- :class:`features_selection.SelectFromModel` now has a ``partial_fit``
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method only if the underlying estimator does. By `Andreas Müller`_.
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- The ``include_others`` and ``dont_test`` parameters of :func:`utils.testing.all_estimators` are deprecated
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and are assumed ``True``, by `Andreas Müller`_.
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- :class:`dummy.DummyClassifier` and :class:`dummy.DummyRegressor` now do
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input validation on ``X`` and check whether ``X`` and ``y`` are of the
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same length, by `Andreas Müller`_.
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- :class:`multiclass.OneVsRestClassifier` now has a ``partial_fit`` method
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only if the underlying estimator does. By `Andreas Müller`_.
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- :class:`dummy.DummyClassifier` and :class:`dummy.DummyRegressor` now do input validation on ``X`` and check
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whether ``X`` and ``y`` are of the same length, by `Andreas Müller`_.
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- :class:`multiclass.OneVsRestClassifier` now has a ``partial_fit`` method only if the underlying estimator does.
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By `Andreas Müller`_.
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.. _changes_0_18_1:
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Version 0.18.1

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