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https://issues.apache.org/jira/browse/SPARK-14610?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15240274#comment-15240274
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Apache Spark commented on SPARK-14610:
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User 'sethah' has created a pull request for this issue:
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
>
> 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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