[jira] [Commented] (MAHOUT-1493) Port Naive Bayes to the Spark DSL

["Andrew Palumbo (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAHOUT-1493?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14064027#comment-14064027 ] 

Andrew Palumbo commented on MAHOUT-1493:
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[~cviebig], The patch looks good. I've made some edits (against your branch) and will attach an M-1493a.patch shortly.  I put the trainComplementary parameter back in as this is needed to make the distinction between Standard and Complementary Models in the NaiveBayesModel constructor.  

As well, I've added a thetaNormalizer var which can remain null when passed to the NaiveBayesModel constructor unless training a Complementary NB model. see:
 
https://github.com/apache/mahout/blob/master/mrlegacy/src/main/java/org/apache/mahout/classifier/naivebayes/NaiveBayesModel.java

I'm not sure if creating a null var as I've done here is best practice in scala, but i wanted to give you an idea of the NaiveBayesModel design.  

As you've noted, there has been a lot of refactoring going on.  As far as moving the code, I think that for now it might be a good idea to keep this in `spark` module, and move the `org.apache.mahout.sparkbindings.drm.classification` package out of `org.apache.mahout.sparkbindings.drm` and into a new `org.apache.mahout.classification` package.  I believe that for now this would be a good place for it.  There shouldn't be any need to move any of the java code from mrlegacy.


 



> Port Naive Bayes to the Spark DSL
> ---------------------------------
>
>                 Key: MAHOUT-1493
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1493
>             Project: Mahout
>          Issue Type: Bug
>          Components: Classification
>            Reporter: Sebastian Schelter
>            Assignee: Sebastian Schelter
>             Fix For: 1.0
>
>         Attachments: 1493a.patch, MAHOUT-1493.patch, MAHOUT-1493.patch, MAHOUT-1493.patch, MAHOUT-1493.patch
>
>
> Port our Naive Bayes implementation to the new spark dsl. Shouldn't require more than a few lines of code.



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