[jira] [Resolved] (SPARK-14610) Remove superfluous split from random forest findSplitsForContinousFeature

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14610?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-14610.
---------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

Issue resolved by pull request 12374
[https://github.com/apache/spark/pull/12374]

> Remove superfluous split from random forest findSplitsForContinousFeature
> -------------------------------------------------------------------------
>
>                 Key: SPARK-14610
>                 URL: https://issues.apache.org/jira/browse/SPARK-14610
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Seth Hendrickson
>            Assignee: Seth Hendrickson
>            Priority: Minor
>             Fix For: 2.1.0
>
>
> Currently, the method findSplitsForContinuousFeature in random forest produces an unnecessary split. For example, if a continuous feature has unique values: (1, 2, 3), then the possible splits generated by this method are:
> * {1|2,3}
> * {1,2|3} 
> * {1,2,3|}
> The following unit test is quite clearly incorrect:
> {code:title=rf.scala|borderStyle=solid}
> val featureSamples = Array(1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3).map(_.toDouble)
>       val splits = RandomForest.findSplitsForContinuousFeature(featureSamples, fakeMetadata, 0)
>       assert(splits.length === 3)
> {code}



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