title: How to get accuracy precision, recall and ROC from cross validation in Spark ml lib?
body: <p>I am using Spark 2.0.2. I am also using the "ml" library for Machine Learning with Datasets. What I want to do is run algorithms with cross validation and extract the mentioned metrics (accuracy, precision, recall, ROC, confusion matrix). My data labels are binary.</p>
  
  <p>By using the MulticlassClassificationEvaluator I can only get the accuracy of the algorithm by accessing "avgMetrics". Also, by using the BinaryClassificationEvaluator I can get the area under ROC. But I cannot use them both. 
  So, is there a way that I can extract all of the wanted metrics?</p>