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From "Qiping Li (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-3272) Calculate prediction for nodes separately from calculating information gain for splits in decision tree
Date Sat, 30 Aug 2014 05:42:52 GMT

    [ https://issues.apache.org/jira/browse/SPARK-3272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14116247#comment-14116247
] 

Qiping Li commented on SPARK-3272:
----------------------------------

Hi Joseph,
I have clarified in [SPARK-2207|https://issues.apache.org/jira/browse/SPARK-2207] to implement
(b),
thanks for your support, I will try my best to make it useful.
I will continue with this after you PR(https://github.com/apache/spark/pull/2125) is merged.

> 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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