title: Spark CrossValidatorModel access other models than the bestModel?
body: <p>I am using Spark 1.6.1:</p>
  
  <p>Currently I am using a CrossValidator to train my ML Pipeline with various parameters. After the training process I can use the bestModel property of the CrossValidatorModel to get the Model that performed best during the Cross Validation.
  Are the other models of the cross validation automatically discarded or can I select a model that performed worse than the bestModel?</p>
  
  <p>I am asking because I am using the F1 Score metric for the cross validation but I am also interested in the weighedRecall of all of the models and not just of the model that has performed best during the crossvalidation</p>
  
  <pre><code>val folds = 6
  val cv = new CrossValidator()
    .setEstimator(pipeline)
    .setEvaluator(new MulticlassClassificationEvaluator)
    .setEstimatorParamMaps(paramGrid)
    .setNumFolds(folds)
  
  val avgF1Scores = cvModel.avgMetrics
  
  val predictedDf = cvModel.bestModel.transform(testDf)
  
  // Here I would like to predict as well with the other models of the cross validation
  </code></pre>