8000 DOC Ensures that train_test_split passes numpydoc validation (#21435) · samronsin/scikit-learn@ab65528 · GitHub
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DOC Ensures that train_test_split passes numpydoc validation (scikit-learn#21435)
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maint_tools/test_docstrings.py

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@@ -172,7 +172,6 @@
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"sklearn.metrics.pairwise.rbf_kernel",
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"sklearn.metrics.pairwise.sigmoid_kernel",
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"sklearn.model_selection._split.check_cv",
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"sklearn.model_selection._split.train_test_split",
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"sklearn.model_selection._validation.cross_val_score",
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"sklearn.model_selection._validation.cross_validate",
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"sklearn.model_selection._validation.learning_curve",

sklearn/model_selection/_split.py

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@@ -2326,7 +2326,7 @@ def train_test_split(
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shuffle=True,
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stratify=None,
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):
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"""Split arrays or matrices into random train and test subsets
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"""Split arrays or matrices into random train and test subsets.
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Quick utility that wraps input validation and
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``next(ShuffleSplit().split(X, y))`` and application to input data
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Pass an int for reproducible output across multiple function calls.
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See :term:`Glossary <random_state>`.
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shuffle : bool, default=True
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Whether or not to shuffle the data before splitting. If shuffle=False
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then stratify must be None.
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>>> train_test_split(y, shuffle=False)
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[[0, 1, 2], [3, 4]]
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"""
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n_arrays = len(arrays)
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if n_arrays == 0:

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