[jira] [Assigned] (SPARK-13712) Add OneVsOne to ML

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-13712?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-13712:
------------------------------------

    Assignee:     (was: Apache Spark)

> Add OneVsOne to ML
> ------------------
>
>                 Key: SPARK-13712
>                 URL: https://issues.apache.org/jira/browse/SPARK-13712
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: zhengruifeng
>            Priority: Minor
>
> Another Meta method for multi-class classification.
> Most classification algorithms were designed for balanced data.
> The OneVsRest method will generate K models on imbalanced data.
> The OneVsOne will train K*(K-1)/2 models on balanced data.
> OneVsOne is less sensitive to the problems of imbalanced datasets, and can usually result in higher precision.
> But it is much more computationally expensive, although each model are trained on a much smaller dataset. (2/K of total)
> The OneVsOne is implemented in the way OneVsRest did:
> val classifier = new LogisticRegression()
> val ovo = new OneVsOne()
> ovo.setClassifier(classifier)
> val ovoModel = ovo.fit(data)
> val predictions = ovoModel.transform(data)



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