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I have heard approaches described that train a simpler ML algorithm to predict why a complex ML algorithm made a decision. Decision-tree models predicting neura
by philipodonnell 9y ago
I have heard approaches described that train a simpler ML algorithm to predict why a complex ML algorithm made a decision. Decision-tree models predicting neural net models. Paypal or Square I believe.
- vinn124 9y agohow does this solve anything? if a simple decision tree could predict the outputs of more complex deep nets, why not use the decision tree in the first place? also, what do you do when a decision tree isnt powerful enough, as in the case of many interesting problems such as speech, computer vision, etc.
- philipodonnell 9y agoThe uses cases for this were around fraud detection systems where you need to provide a reason for the flag. I don't have to know the complexities of how all the factors are interacting within a neural net to be able to tell someone that if they increased their credit score by 100 points, they'd be approved.