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https://issues.apache.org/jira/browse/SPARK-14975?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-14975:
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Affects Version/s: (was: 1.6.1)
> Predicted Probability per training instance for Gradient Boosted Trees in
> mllib.
> ---------------------------------------------------------------------------------
>
> Key: SPARK-14975
> URL: https://issues.apache.org/jira/browse/SPARK-14975
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Partha Talukder
> Priority: Minor
> Labels: mllib
>
> This function available for Logistic Regression, SVM etc.
> (model.setThreshold()) but not for GBT. In comparison to "gbm" package in R,
> where we can specify the distribution and get predicted probabilities or
> classes. I understand that this algorithm works with "Classification" and
> "Regression" algo's. Is there any way where in GBT we can get predicted
> probabilities or provide thresholds to the model?
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