8000 ENH Sample weights for ElasticNetCV (#16449) · samronsin/scikit-learn@fee3b44 · GitHub
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ENH Sample weights for ElasticNetCV (scikit-learn#16449)
Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org> Co-authored-by: Christian Lorentzen <lorentzen.ch@googlemail.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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‎doc/whats_new/v1.0.rst

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complexity in the number of samples.
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:pr:`10027` by :user:`Albert Thomas <albertcthomas>`.
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- |Feature| Added `sample_weight` parameter to
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:class:`linear_model.LassoCV` and :class:`linear_model.ElasticNetCV`.
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:pr:`16449` by :user:`Christian Lorentzen <lorentzenchr>`.
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- |Efficiency| The implementation of :class:`linear_model.LogisticRegression`
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has been optimised for dense matrices when using `solver='newton-cg'` and
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`multi_class!='multinomial'`.
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and :user:`Oliver Grisel <ogrisel>`.
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- |Feature| :func:`metrics.mean_squared_log_error` now supports
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`squared=False`.
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`squared=False`.
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:pr:`20326` by :user:`Uttam kumar <helper-uttam>`.
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- |Efficiency| Improved speed of :func:`metrics.confusion_matrix` when labels
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are integral.
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:pr:`9843` by :user:`Jon Crall <Erotemic>`.

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