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https://issues.apache.org/jira/browse/SPARK-5133?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Peter Prettenhofer updated SPARK-5133:
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Summary: Feature Importance for Decision Tree (Ensembles) (was: Feature
Importance for Tree (Ensembles))
> Feature Importance for Decision Tree (Ensembles)
> ------------------------------------------------
>
> Key: SPARK-5133
> URL: https://issues.apache.org/jira/browse/SPARK-5133
> Project: Spark
> Issue Type: New Feature
> Components: ML, MLlib
> Reporter: Peter Prettenhofer
> Priority: Minor
>
> Add feature importance to decision tree model and tree ensemble models.
> If people are interested in this feature I could implement it given a mentor
> (API decisions, etc). Please find a description of the feature below:
> Decision trees intrinsically perform feature selection by selecting
> appropriate split points. This information can be used to assess the relative
> importance of a feature.
> Relative feature importance gives valuable insight into a decision tree or
> tree ensemble and can even be used for feature selection.
> All necessary information to create relative importance scores should be
> available in the tree representation (class Node; split, impurity gain,
> (weighted) nr of samples?).
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