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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2017/09/02 00:33:04 UTC
[jira] [Resolved] (SPARK-21729) Generic test for
ProbabilisticClassifier to ensure consistent output columns
[ https://issues.apache.org/jira/browse/SPARK-21729?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley resolved SPARK-21729.
---------------------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
Issue resolved by pull request 19065
[https://github.com/apache/spark/pull/19065]
> Generic test for ProbabilisticClassifier to ensure consistent output columns
> ----------------------------------------------------------------------------
>
> Key: SPARK-21729
> URL: https://issues.apache.org/jira/browse/SPARK-21729
> Project: Spark
> Issue Type: Test
> Components: ML
> Affects Versions: 2.2.0
> Reporter: Joseph K. Bradley
> Assignee: Weichen Xu
> Fix For: 2.3.0
>
>
> One challenge with the ProbabilisticClassifier abstraction is that it introduces different code paths for predictions depending on which output columns are turned on or off: probability, rawPrediction, prediction. We ran into a bug in MLOR with this.
> This task is for adding a generic test usable in all test suites for ProbabilisticClassifier types which does the following:
> * Take a dataset + Estimator
> * Fit the Estimator
> * Test prediction using the model with all combinations of output columns turned on/off.
> * Make sure the output column values match, presumably by comparing vs. the case with all 3 output columns turned on
> CC [~WeichenXu123] since this came up in https://github.com/apache/spark/pull/17373
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