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https://issues.apache.org/jira/browse/SPARK-4894?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14279241#comment-14279241
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Joseph K. Bradley commented on SPARK-4894:
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[~rnowling] I too don't want to hold up the Bernoulli NB too much. I just
made & linked a JIRA per your suggestion
[https://issues.apache.org/jira/browse/SPARK-5272]. I'll add my thoughts there
(and feel free to copy yours there too).
I'm not sure if we can reuse much from decision trees since they are not
probabilistic models and have a different concept of "loss" or "error."
For now, generalizing the existing Naive Bayes class to handle the Bernoulli
case sounds good. Thanks for taking the time to discuss this!
> Add Bernoulli-variant of Naive Bayes
> ------------------------------------
>
> Key: SPARK-4894
> URL: https://issues.apache.org/jira/browse/SPARK-4894
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.2.0
> Reporter: RJ Nowling
> Assignee: RJ Nowling
>
> MLlib only supports the multinomial-variant of Naive Bayes. The Bernoulli
> version of Naive Bayes is more useful for situations where the features are
> binary values.
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