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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/03/29 07:25:25 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 ]
Joseph K. Bradley updated SPARK-14216:
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Summary: ML tree models should have a standardized, reusable feature importance test (was: ML models should have a standardized, reusable feature importance test)
> 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
>
> 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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