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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/08/14 02:41:45 UTC
[jira] [Updated] (SPARK-9956) Spark ML trees and ensembles fail for
categorical features with 1 category
[ https://issues.apache.org/jira/browse/SPARK-9956?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-9956:
-------------------------------------
Issue Type: Bug (was: Improvement)
> 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
>
> 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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