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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