Hi ml folks ! I'm using a Random Forest for a binary classification. I'm interested in getting both the ROC *curve* and the feature importance from the trained model.
If I'm not missing something obvious, the ROC curve is only available in the old mllib world, via BinaryClassificationMetrics. In the new ml package, only the areaUnderROC and areaUnderPR are available through BinaryClassificationEvaluator. The feature importance is only available in ml package, through RandomForestClassificationModel. Any idea to get both ? Mathieu -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Get-both-feature-importance-and-ROC-curve-from-a-random-forest-classifier-tp27175.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
