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https://issues.apache.org/jira/browse/SPARK-8069?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14571549#comment-14571549
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Joseph K. Bradley commented on SPARK-8069:
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For others who look at this JIRA, the "cutoff" is analogous to the "threshold"
used by MLlib's LogisticRegressionModel, especially useful to adjust the
classification model's location on a ROC curve.
This JIRA is relevant to all multiclass classifiers. It would be nice if we
could think of a good way to implement this functionality within the
ClassificationModel abstraction in spark.ml to avoid code duplication (but only
if it actually simplifies/standardizes things).
> Add support for cutoff to RandomForestClassifier
> ------------------------------------------------
>
> Key: SPARK-8069
> URL: https://issues.apache.org/jira/browse/SPARK-8069
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: holdenk
> Priority: Minor
>
> Consider adding support for cutoffs similar to
> http://cran.r-project.org/web/packages/randomForest/randomForest.pdf
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