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https://issues.apache.org/jira/browse/SPARK-4766?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley resolved SPARK-4766.
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Resolution: Won't Fix
Assignee: Joseph K. Bradley
Target Version/s: (was: 1.4.0)
> ML Estimator Params should be distinct from Transformer Params
> --------------------------------------------------------------
>
> Key: SPARK-4766
> URL: https://issues.apache.org/jira/browse/SPARK-4766
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 1.2.0
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
>
> Currently, in spark.ml, both Transformers and Estimators extend the same
> Params classes. There should be one Params class for the Transformer and one
> for the Estimator. These could sometimes be the same, but for other models,
> we may need either (a) to make them distinct or (b) to have the Estimator
> params class extend the Transformer one.
> E.g., it is weird to be able to do:
> {code}
> val model: LogisticRegressionModel = ...
> model.getMaxIter()
> {code}
> It's also weird to be able to:
> * Wrap LogisticRegressionModel (a Transformer) with CrossValidator
> * Pass a set of ParamMaps to CrossValidator which includes parameter
> LogisticRegressionModel.maxIter
> * (CrossValidator would try to set that parameter.)
> * I'm not sure if this would cause a failure or just be a noop.
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