[ https://issues.apache.org/jira/browse/SPARK-9961?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-9961: ------------------------------------- Description: Predictor and PredictionModel should have abstract defaultEvaluator methods which return Evaluators. Subclasses like Regressor, Classifier, etc. should all provide natural evaluators, set to use the correct input columns and metrics. Concrete classes may later be modified to use other evaluators or evaluator options. The initial implementation should be marked as DeveloperApi since we may need to change the defaults later on. was: Predictor and PredictionModel should have abstract defaultEvaluator methods which return Evaluators. Subclasses like Regressor, Classifier, etc. should all provide natural evaluators, set to use the correct input columns and metrics. Concrete classes may later be modified to The initial implementation should be marked as DeveloperApi since we may need to change the defaults later on. > ML prediction abstractions should have defaultEvaluator fields > -------------------------------------------------------------- > > Key: SPARK-9961 > URL: https://issues.apache.org/jira/browse/SPARK-9961 > Project: Spark > Issue Type: New Feature > Components: ML > Reporter: Joseph K. Bradley > > Predictor and PredictionModel should have abstract defaultEvaluator methods > which return Evaluators. Subclasses like Regressor, Classifier, etc. should > all provide natural evaluators, set to use the correct input columns and > metrics. Concrete classes may later be modified to use other evaluators or > evaluator options. > The initial implementation should be marked as DeveloperApi since we may need > to change the defaults later on. -- 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