Hey, Is there some kind of "explain" feature implemented in mllib for the algorithms based on tree ensembles? Some method to which you would feed in a single feature vector and it would return/print what features contributed to the decision or how much each feature contributed "negatively" and "positively" to the decision.
This can be very useful to debug a model on some specific samples and for feature engineering. Thanks, Eugen
