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Hi team,
As I'm testing the treeinterpreter module for random forest from the home example code, the last code for examing the random forest prediction and using the interpreter results with bias + np.sum(contributions, axis=1). I think it's not right by using the rf.predict function to get the prediction, correct way should use the rf.predict_proba() function to get the probability, right? As sklearn will convert the probability with argmax to get the index as label for prediction.
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