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From "Villu Ruusmann (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
Date Thu, 25 Jun 2015 21:54:04 GMT

    [ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14602023#comment-14602023
] 

Villu Ruusmann commented on SPARK-8546:
---------------------------------------

The NB exporter should be easier to implement than Logistic regression and SVM exporters,
because the PMML representation of NB models does not distinguish between binary and multi-class
classification cases.

I'm currently developing PMML exporters for the Python ML module called Scikit-Learn. Unfortunately,
I haven't made to Scikit-Learn classes GaussianNB and MultinomialNB yet. I shall be much wiser
once I get them done.

> PMML export for Naive Bayes
> ---------------------------
>
>                 Key: SPARK-8546
>                 URL: https://issues.apache.org/jira/browse/SPARK-8546
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Joseph K. Bradley
>            Priority: Minor
>
> The naive Bayes section of PMML standard can be found at http://www.dmg.org/v4-1/NaiveBayes.html.
We should first figure out how to generate PMML for both binomial and multinomial naive Bayes
models using JPMML (maybe [~vfed] can help).



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