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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.
The text was updated successfully, but these errors were encountered:
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 therf.predict
function to get the prediction, correct way should use therf.predict_proba()
function to get the probability, right? As sklearn will convert the probability withargmax
to get the index as label for prediction.The text was updated successfully, but these errors were encountered: