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Posted to issues@spark.apache.org by "Partha Talukder (JIRA)" <ji...@apache.org> on 2016/04/28 09:39:12 UTC

[jira] [Created] (SPARK-14975) Predicted Probability per training instance for Gradient Boosted Trees in mllib.

Partha Talukder created SPARK-14975:
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             Summary: 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
    Affects Versions: 1.6.1
            Reporter: Partha Talukder


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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