[ https://issues.apache.org/jira/browse/SPARK-14975?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-14975: ------------------------------------ Assignee: (was: Apache Spark) > 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: New Feature > 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? -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org