Documentation for #10772 MultinomialNB alpha>0#10775
Documentation for #10772 MultinomialNB alpha>0#10775bhaskarb wants to merge 1 commit intoscikit-learn:mainfrom
Conversation
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Thanks for this PR @bhaskarb
scikit-learn/sklearn/naive_bayes.py Line 645 in 011c0b3 also would need to be changed (and same for But then I'm not sure what should be said there... "set to a small positive number to disable smoothing" doesn't sound right. I'm not sure if raising a warning for alpha=0 is such a good thing in the first place. On one side, it's understandable to warn the user but it's also unreasobable to expect him/her to enter a small value that is close enough to zero to disable smoothing but large enough to avoid the warning. I could be worth waiting for a second opinion on this. |
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I would allow alpha=0 and warn / error if we divide by zero later? |
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Closing as superseded by #22269. |
Reference Issues/PRs
Documentation for BernoulliNB and MultinomialNB documentation for alpha=0
Partially fixes issue #10772
What does this implement/fix? Explain your changes.
The MultinomialNB cannot have an alpha = 0, it originally set alpha>=0 and i changed it to alpha>0
Any other comments?