In order to build a predict model with two categories (buy or not buy),I want to use RandomForest and predict with type='prob', so I can have a prob of someone buy or not buy. So, with this outcome I can clusterize and make groups, like this:
group A: costumer who has [100 to 80]% of buy. group B: costumer who has [81 to 60]% of buy. ...
But I don't know the appropriate evaluation metric to measure the accuracy of this model. I guess that I can't use a confusion matrix.
Maybe I can use a ROC curve, and or measure KS between the buy group with the not buy group. But I'm not sure about this metrics.