ENH Adding variable force_alpha to classes in naive_bayes.py
#22269
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…ernoulliNB-and-MultinomialNB-when-alpha-is-close-or-equal-0 # Conflicts: # doc/whats_new/v0.24.rst # sklearn/naive_bayes.py
# Conflicts: # doc/whats_new/v1.0.rst
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
# Conflicts: # sklearn/naive_bayes.py
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thomasjpfan
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This reverts commit 14a360f.
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
force_alpha to classes in naive_bayes.pyforce_alpha to classes in naive_bayes.py
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Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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The NaiveBayes classifiers now have a force_alpha attribute, which is explained in: scikit-learn/scikit-learn#22269 This PR just gets the code working; it would be good to invest some time into reading the details of that sklearn PR and making the appropriate adjustments.
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Reference Issues/PRs
Fixes #10772
Resolves #10775 (stalled)
Resolves #16747 (stalled)
Resolves #18805 (stalled)
What does this implement/fix? Explain your changes.
This PR takes over stalled PR #18805.
From the description of #16747 and #18805: "This PR adds a new variable
alphaCorrectionin classes innaive_bayes.py, which is set toTrueby default and if set toFalse, then foralpha=0(or greater, but still smaller than_ALPHA_MIN) alpha is not being rounded up to_ALPHA_MIN."This PR updated minor version details in documentation as well as began a double-deprecation cycle, initially adding a
force_alpha=Falsekeyword and begins a deprecation cycle to change its default toTrue. After completion of this default change, a new deprecation cycle will begin to removeforce_alpha.Any other comments?
Follow-up PR to begin deprecation for removal of
force_alpha