[jira] [Resolved] (SPARK-9956) Spark ML trees and ensembles fail for categorical features with 1 category

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-9956?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley resolved SPARK-9956.
--------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.5.0

Issue resolved by pull request 8187
[https://github.com/apache/spark/pull/8187]

> Spark ML trees and ensembles fail for categorical features with 1 category
> --------------------------------------------------------------------------
>
>                 Key: SPARK-9956
>                 URL: https://issues.apache.org/jira/browse/SPARK-9956
>             Project: Spark
>          Issue Type: Bug
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Assignee: Joseph K. Bradley
>             Fix For: 1.5.0
>
>
> Spark ML trees and ensembles can be given metadata (e.g., from VectorIndexer) indicating that a certain feature is categorical with a single possible value.  This causes learning to fail.
> Proposal: For now, fix this by making sure the algorithm still runs with such a feature, and remove the checks (which currently cause failure).  In the future, we can filter out these features to improve performance when there are many useless features.



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