Github user petro-rudenko commented on the pull request:
https://github.com/apache/spark/pull/3637#issuecomment-71636977
Also would be nice to be able to get/set model state:
```scala
// Run cross-validation, and choose the best set of parameters.
val cvModel = crossval.fit(training)
val modelState = cvModel.bestModel.getModelState
// Map(weights-> Vector(0.2, 0.3, 0.5,...), regParam -> 0.1, ...)
//Save this state, pass to other prediction frontend, etc.
val lr = new LogisticRegression()
val lrModel = lr.setModelState(modelState)
//LogisticRegressionModel
lrModel.transform(...).predict(...)
```
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