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[DOC] Update random_state descriptions for SVMs #16316

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Jan 31, 2020
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[DOC] Update random_state descriptions for SVMs #16316

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a507d83
Update svm random_state doc
DatenBiene Jan 30, 2020
932c600
Update doc
DatenBiene Jan 30, 2020
424d589
Update svm random_state doc
DatenBiene Jan 31, 2020
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8 changes: 3 additions & 5 deletions sklearn/svm/_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -861,11 +861,9 @@ def _fit_liblinear(X, y, C, fit_intercept, intercept_scaling, class_weight,
Stopping condition.

random_state : int or RandomState instance, default=None
The seed of the pseudo random number generator to use when shuffling
the data. If int, random_state is the seed used by the random number
generator; If RandomState instance, random_state is the random number
generator; If None, the random number generator is the RandomState
instance used by `np.random`.
Controls the pseudo random number generation for shuffling the data.
Pass an int for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

multi_class : {'ovr', 'crammer_singer'}, default='ovr'
`ovr` trains n_classes one-vs-rest classifiers, while `crammer_singer`
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40 changes: 17 additions & 23 deletions sklearn/svm/_classes.py
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Expand Up @@ -89,14 +89,12 @@ class LinearSVC(BaseEstimator, LinearClassifierMixin,
properly in a multithreaded context.

random_state : int or RandomState instance, default=None
The seed of the pseudo random number generator to use when shuffling
the data for the dual coordinate descent (if ``dual=True``). When
``dual=False`` the underlying implementation of :class:`LinearSVC`
is not random and ``random_state`` has no effect on the results. If
int, random_state is the seed used by the random number generator; If
RandomState instance, random_state is the random number generator; If
None, the random number generator is the RandomState instance used by
`np.random`.
Controls the pseudo random number generation for shuffling the data for
the dual coordinate descent (if ``dual=True``). When ``dual=False`` the
underlying implementation of :class:`LinearSVC` is not random and
``random_state`` has no effect on the results.
Pass an int for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

max_iter : int, default=1000
The maximum number of iterations to be run.
Expand Down Expand Up @@ -300,11 +298,9 @@ class LinearSVR(RegressorMixin, LinearModel):
properly in a multithreaded context.

random_state : int or RandomState instance, default=None
The seed of the pseudo random number generator to use when shuffling
the data. If int, random_state is the seed used by the random number
generator; If RandomState instance, random_state is the random number
generator; If None, the random number generator is the RandomState
instance used by `np.random`.
Controls the pseudo random number generation for shuffling the data.
Pass an int for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

max_iter : int, default=1000
The maximum number of iterations to be run.
Expand Down Expand Up @@ -522,11 +518,10 @@ class SVC(BaseSVC):
.. versionadded:: 0.22

random_state : int or RandomState instance, default=None
The seed of the pseudo random number generator used when shuffling
the data for probability estimates. If int, random_state is the
seed used by the random number generator; If RandomState instance,
random_state is the random number generator; If None, the random
number generator is the RandomState instance used by `np.random`.
Controls the pseudo random number generation for shuffling the data for
probability estimates.
Pass an int for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

Attributes
----------
Expand Down Expand Up @@ -728,11 +723,10 @@ class NuSVC(BaseSVC):
.. versionadded:: 0.22

random_state : int or RandomState instance, default=None
The seed of the pseudo random number generator used when shuffling
the data for probability estimates. If int, random_state is the seed
used by the random number generator; If RandomState instance,
random_state is the random number generator; If None, the random
number generator is the RandomState instance used by `np.random`.
Controls the pseudo random number generation for shuffling the data for
probability estimates.
Pass an int for reproducible output across multiple function calls.
See :term:`Glossary <random_state>`.

Attributes
----------
Expand Down