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From "Joseph K. Bradley (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-3727) Trees and ensembles: More prediction functionality
Date Thu, 20 Aug 2015 04:02:47 GMT

     [ https://issues.apache.org/jira/browse/SPARK-3727?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Joseph K. Bradley updated SPARK-3727:
-------------------------------------
    Shepherd: Joseph K. Bradley

> 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.



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