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https://issues.apache.org/jira/browse/SPARK-17697?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15534847#comment-15534847
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Joseph K. Bradley commented on SPARK-17697:
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Leaving open for follow-up to fix all GLM issues
> BinaryLogisticRegressionSummary, GLM Summary should handle non-Double numeric
> types
> -----------------------------------------------------------------------------------
>
> Key: SPARK-17697
> URL: https://issues.apache.org/jira/browse/SPARK-17697
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.0.1, 2.1.0
> Reporter: Joseph K. Bradley
> Assignee: Bryan Cutler
>
> Say you have a DataFrame with a label column of Integer type. You can fit a
> LogisticRegresionModel since LR handles casting to DoubleType internally.
> However, if you call evaluate() on it, then this line does not handle casting
> properly, so you get a runtime error (MatchError) for an invalid schema:
> [https://github.com/apache/spark/blob/2cd327ef5e4c3f6b8468ebb2352479a1686b7888/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala#L863]
> We should handle casting. And test evaluate() with other numeric types.
> **ALSO** We should check elsewhere in logreg and other algorithms to see if
> we can catch the same issue elsewhere.
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