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From jkbradley <...@git.apache.org>
Subject [GitHub] spark pull request #19208: [SPARK-21087] [ML] CrossValidator, TrainValidatio...
Date Mon, 13 Nov 2017 18:14:18 GMT
Github user jkbradley commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19208#discussion_r150619165
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala ---
    @@ -265,23 +317,58 @@ class TrainValidationSplitModel private[ml] (
     @Since("2.0.0")
     object TrainValidationSplitModel extends MLReadable[TrainValidationSplitModel] {
     
    +  private[TrainValidationSplitModel] def copySubModels(subModels: Option[Array[Model[_]]])
    +    : Option[Array[Model[_]]] = {
    +    subModels.map(_.map(_.copy(ParamMap.empty).asInstanceOf[Model[_]]))
    +  }
    +
       @Since("2.0.0")
       override def read: MLReader[TrainValidationSplitModel] = new TrainValidationSplitModelReader
     
       @Since("2.0.0")
       override def load(path: String): TrainValidationSplitModel = super.load(path)
     
    -  private[TrainValidationSplitModel]
    -  class TrainValidationSplitModelWriter(instance: TrainValidationSplitModel) extends
MLWriter {
    +  /**
    +   * Writer for TrainValidationSplitModel.
    +   * @param instance TrainValidationSplitModel instance used to construct the writer
    +   *
    +   * TrainValidationSplitModel supports an option "persistSubModels", with possible values
    +   * "true" or "false". If you set the collectSubModels Param before fitting, then you
can
    +   * set "persistSubModels" to "true" in order to persist the subModels. By default,
    +   * "persistSubModels" will be "true" when subModels are available and "false" otherwise.
    +   * If subModels are not available, then setting "persistSubModels" to "true" will cause
    +   * an exception.
    +   */
    +  final class TrainValidationSplitModelWriter private[tuning] (
    --- End diff --
    
    Since annotation


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