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It's pretty hard to return "rules" for a ML system, especially a non-linear system. Google is currently working systems that use a trillion features - I can't imagine returning some kind of rule list for that.

LIME[1] is a nice start, though.

[1] https://www.oreilly.com/learning/introduction-to-local-inter...




Another text about interpreting convolutional neural networks:

http://cs231n.github.io/understanding-cnn/

> Google is currently working systems that use a trillion features - I can't imagine returning some kind of rule list for that.

As I wrote: It would already help if the ML system as a first step returned the derivation with only the rules that were concretely used for a concrete derivation - this list is much shorter and can thus much easier be checked.




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