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Joseph K. Bradley commented on SPARK-3727: ------------------------------------------ [~maxkaznady] Implementations should be done in Scala; the PySpark API will be a wrapper. The API update JIRA I'm referencing should clear up some of the other questions. > Trees and ensembles: More prediction functionality > -------------------------------------------------- > > Key: SPARK-3727 > URL: https://issues.apache.org/jira/browse/SPARK-3727 > Project: Spark > Issue Type: Improvement > Components: MLlib > Reporter: Joseph K. Bradley > > DecisionTree and RandomForest currently predict the most likely label for > classification and the mean for regression. Other info about predictions > would be useful. > For classification: estimated probability of each possible label > For regression: variance of estimate > RandomForest could also create aggregate predictions in multiple ways: > * Predict mean or median value for regression. > * Compute variance of estimates (across all trees) for both classification > and regression. -- 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