title: Evaluate Random Forest performance using R-Squared
body: <p>I'm looking to evaluate test performance of a random forest regressor in Python and, in addition to running cross-validation on the training-set, am wondering if it is appropriate to run some sort of correlation analysis between the predicted Y test results and the actual Y test results? </p>
  
  <p>My possibly oversimplified thinking being that a significant correlation between the two would indicate that the predicted Y's are aligned with the actual test Y's and, as such, predictions are good...</p>
  
  <p>Any alternative suggestions are more than welcome. Thanks.</p>