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https://issues.apache.org/jira/browse/SPARK-21770?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16150846#comment-16150846
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Joseph K. Bradley commented on SPARK-21770:
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Linear models are the most likely to hit this case; if the algorithm has done 0
iterations, then all coefficients will be 0. But I agree it's just fixing a
corner case which few people would ever hit. OK to fix though IMO.
> ProbabilisticClassificationModel: Improve normalization of all-zero raw
> predictions
> -----------------------------------------------------------------------------------
>
> Key: SPARK-21770
> URL: https://issues.apache.org/jira/browse/SPARK-21770
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.3.0
> Reporter: Siddharth Murching
> Priority: Minor
>
> Given an n-element raw prediction vector of all-zeros,
> ProbabilisticClassifierModel.normalizeToProbabilitiesInPlace() should output
> a probability vector of all-equal 1/n entries
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