Thank you very much for this library, it is exactly what I was looking for.
I noticed there is a difference in the required arguments of two methods of the model CostSensitiveRandomForestClassifier, predict and predict_proba. The former accepts a cost matrix as input but the latter does not while I thought they are essentially the same with predict giving a crisp label if the predicted probability (or voting result) is greater than the default threshold of 0.5. Can you explain if I'm missing something here ?
Hi,
Thank you very much for this library, it is exactly what I was looking for.
I noticed there is a difference in the required arguments of two methods of the model CostSensitiveRandomForestClassifier, predict and predict_proba. The former accepts a cost matrix as input but the latter does not while I thought they are essentially the same with predict giving a crisp label if the predicted probability (or voting result) is greater than the default threshold of 0.5. Can you explain if I'm missing something here ?
Thanks.