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https://issues.apache.org/jira/browse/SPARK-3272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14126799#comment-14126799
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Apache Spark commented on SPARK-3272:
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User 'chouqin' has created a pull request for this issue:
https://github.com/apache/spark/pull/2332
> Calculate prediction for nodes separately from calculating information gain
> for splits in decision tree
> -------------------------------------------------------------------------------------------------------
>
> Key: SPARK-3272
> URL: https://issues.apache.org/jira/browse/SPARK-3272
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.0.2
> Reporter: Qiping Li
> Fix For: 1.1.0
>
>
> In current implementation, prediction for a node is calculated along with
> calculation of information gain stats for each possible splits. The value to
> predict for a specific node is determined, no matter what the splits are.
> To save computation, we can first calculate prediction first and then
> calculate information gain stats for each split.
> This is also necessary if we want to support minimum instances per node
> parameters([SPARK-2207|https://issues.apache.org/jira/browse/SPARK-2207])
> because when all splits don't satisfy minimum instances requirement , we
> don't use information gain of any splits. There should be a way to get the
> prediction value.
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