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https://issues.apache.org/jira/browse/SPARK-3727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14492839#comment-14492839
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Max Kaznady commented on SPARK-3727:
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I implemented the same thing but for PySpark. Since there is no existing
function, should I just call the function "predict_proba" like in sklearn?
Also, does it make sense to open a new ticket for this, since it's so specific?
Thanks,
Max
> DecisionTree, RandomForest: 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.
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