10000 documentation issues: label changed and added for version 0.18 · scikit-learn/scikit-learn@901ef53 · GitHub
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documentation issues: label changed and added for version 0.18
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‎sklearn/cluster/_kmeans.py

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@@ -835,7 +835,8 @@ class KMeans(TransformerMixin, ClusterMixin, BaseEstimator):
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might change in the future for a better heuristic.
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.. versionchanged:: 0.18
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Added ''algorithm="elkan"'' implementing Elkan's fast K-Means algorithm
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Added ''algorithm="elkan"'' implementing Elkan's fast K-Means
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algorithm
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Attributes
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----------

‎sklearn/ensemble/_voting.py

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@@ -233,7 +233,8 @@ def fit(self, X, y, sample_weight=None):
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Sample weights. If None, then samples are equally weighted.
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Note that this is supported only if all underlying estimators
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support sample weights.
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Returns
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‎sklearn/feature_selection/_univariate_selection.py

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@@ -384,7 +384,7 @@ class SelectPercentile(_BaseFilter):
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Default is f_classif (see below "See also"). The default function only
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works with classification tasks.
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percentile : int, optional, default=10
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Percent of features to keep.
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Default is f_classif (see below "See also"). The default function only
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works with classification tasks.
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k : int or "all", optional, default=10
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Number of top features to select.

‎sklearn/preprocessing/_function_transformer.py

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@@ -66,12 +66,12 @@ class FunctionTransformer(TransformerMixin, BaseEstimator):
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kw_args : dict, optional
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Dictionary of additional keyword arguments to pass to func.
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inv_kw_args : dict, optional
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Dictionary of additional keyword arguments to pass to inverse_func.
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Examples
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--------

‎sklearn/svm/_classes.py

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@@ -213,7 +213,7 @@ def fit(self, X, y, sample_weight=None):
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samples. If not provided,
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then each sample is given unit weight.
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samples. If not provided,
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then each sample is given unit weight.
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