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https://issues.apache.org/jira/browse/MAHOUT-1493?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14132871#comment-14132871
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ASF GitHub Bot commented on MAHOUT-1493:
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Github user andrewpalumbo commented on the pull request:
https://github.com/apache/mahout/pull/32#issuecomment-55501933
This is still very much "java in scala", and needs alot of work (not even
sure if what im referring to as the "Combiner" even works . But conceptually
training should work through to NaiveBayesModel on any engine. NaiveBayesModel
is an MRLegacy object.
My thinking is that extractLabelsAndAggregateObservations can be overridden
and optimized for any engine.
> 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: MAHOUT-1493.patch, MAHOUT-1493.patch, MAHOUT-1493.patch,
> MAHOUT-1493.patch, MAHOUT-1493a.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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