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https://issues.apache.org/jira/browse/SPARK-29118?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen reassigned SPARK-29118:
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Assignee: zhengruifeng
> Avoid redundant computation in GMM.transform && GLR.transform
> -------------------------------------------------------------
>
> Key: SPARK-29118
> URL: https://issues.apache.org/jira/browse/SPARK-29118
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 3.0.0
> Reporter: zhengruifeng
> Assignee: zhengruifeng
> Priority: Minor
>
> In SPARK-27944, the computation for output columns with empty name is skipped.
> Now, I find that we can furthermore optimize
> 1, GMM.transform by directly obtaining the prediction(double) from its
> probabilty prediction(vector), like what ProbabilisticClassificationModel and
> ClassificationModel do.
> 2, GLR.transform by obtaining the prediction(double) from its link
> prediction(double)
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