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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:00:26 UTC

[jira] [Updated] (SPARK-14216) ML tree models should have a standardized, reusable feature importance test

     [ https://issues.apache.org/jira/browse/SPARK-14216?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-14216:
---------------------------------
    Labels: bulk-closed  (was: )

> ML tree models should have a standardized, reusable feature importance test
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-14216
>                 URL: https://issues.apache.org/jira/browse/SPARK-14216
>             Project: Spark
>          Issue Type: Test
>          Components: ML, Tests
>            Reporter: Seth Hendrickson
>            Priority: Minor
>              Labels: bulk-closed
>
> ML models that have a {{featureImportances}} attribute all need to perform essentially the same test in their respective testing suites. Currently a fairly primitive test is basically copy/pasted in each test suite. It would be nice to create a single testing method that can be reused for all ML models with feature importance. It would also be nice to increase the robustness of the current test.



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