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https://issues.apache.org/jira/browse/SPARK-1536?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-1536.
----------------------------------
Resolution: Fixed
Fix Version/s: 1.1.0
Issue resolved by pull request 886
[https://github.com/apache/spark/pull/886]
> Add multiclass classification tree support to MLlib
> ---------------------------------------------------
>
> Key: SPARK-1536
> URL: https://issues.apache.org/jira/browse/SPARK-1536
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Manish Amde
> Assignee: Manish Amde
> Priority: Critical
> Fix For: 1.1.0
>
>
> The current decision tree implementation in MLlib only supports binary
> classification. This task involves adding multiclass classification support
> to the decision tree implementation.
> The tasks involves:
> - Choosing a good strategy for multiclass classification among multiple
> options:
> -- add multi class support to impurity but it won't work well with the
> categorical features since the centriod-based ordering assumptions won't hold
> true
> -- error-correcting output codes
> -- one-vs-all
> - Code implementation
> - Unit tests
> - Functional tests
> - Performance tests
> - Documentation
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