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https://issues.apache.org/jira/browse/SPARK-3156?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-3156:
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Assignee: Joseph K. Bradley
> DecisionTree: Order categorical features adaptively
> ---------------------------------------------------
>
> Key: SPARK-3156
> URL: https://issues.apache.org/jira/browse/SPARK-3156
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
>
> Improvement: accuracy
> Currently, ordered categorical features use a fixed bin ordering chosen
> before training based on a subsample of the data. (See the code using
> centroids in findSplitsBins().)
> Proposal: Choose the ordering adaptively for every split. This would require
> a bit more computation on the master, but could improve results by splitting
> more intelligently.
> Required changes: The result of aggregation is used in
> findAggForOrderedFeatureClassification() to compute running totals over the
> pre-set ordering of categorical feature values. The stats should instead be
> used to choose a new ordering of categories, before computing running totals.
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