Github user manishamde commented on the pull request: https://github.com/apache/spark/pull/1290#issuecomment-63375342 @avulanov Thanks for conducting the experiments. Could you plot graphs for the experiments that you conducted with changing number of features and number of machines. It will be good to understand weak scaling (scaling #machines with the size of the dataset) and strong scaling (fixed size dataset with additional machines machine added for speedup) performance. You could look at [strong scaling](https://github.com/apache/spark/pull/79) experiments that @etrain performed for the first decision tree PR for reference. Also, could you compare the accuracy with similar implementation in Python or R? Finally, Decision trees and random forests support multiclass classification.
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