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DOC Fix typos (scikit-learn#31138)
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- array-api-compat and array-api-extra are now vendored within the
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scikit-learn source. Users of the experimental array API standard
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support no longer need to install array-api-compat in their environemnt.
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support no longer need to install array-api-compat in their environment.
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by :user:`Lucas Colley <lucascolley>`

sklearn/externals/array_api_compat/common/_helpers.py

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try:
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bool(x)
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return False
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# The Array API standard dictactes that __bool__ should raise TypeError if the
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# The Array API standard dictates that __bool__ should raise TypeError if the
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# output cannot be defined.
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# Here we allow for it to raise arbitrary exceptions, e.g. like Dask does.
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except Exception:

sklearn/metrics/_classification.py

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The smaller the Brier score loss, the better, hence the naming with "loss".
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The Brier score measures the mean squared difference between the predicted
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probability and the actual outcome. The Brier score is a stricly proper scoring
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probability and the actual outcome. The Brier score is a strictly proper scoring
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rule.
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Read more in the :ref:`User Guide <brier_score_loss>`.

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