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https://issues.apache.org/jira/browse/SPARK-18693?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15786390#comment-15786390
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Devesh Parekh commented on SPARK-18693:
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I suggest this is more appropriately classified as a bug rather than an
improvement. Users who follow the documentation to use CrossValidator for model
selection with these evaluators and weighted input will get wrong results. At
the very least, the user should be warned in the documentation that the results
will be wrong if they fit a weight-aware model on weighted input and use these
existing evaluators in CrossValidator. With that warning in place, making the
evaluators work on weighted input would then be an improvement.
> BinaryClassificationEvaluator, RegressionEvaluator, and
> MulticlassClassificationEvaluator should use sample weight data
> -----------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-18693
> URL: https://issues.apache.org/jira/browse/SPARK-18693
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.0.2
> Reporter: Devesh Parekh
>
> The LogisticRegression and LinearRegression models support training with a
> weight column, but the corresponding evaluators do not support computing
> metrics using those weights. This breaks model selection using CrossValidator.
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