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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/08/14 02:32:46 UTC

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

Joseph K. Bradley created SPARK-9956:
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             Summary: 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: Improvement
          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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