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By the way many methods are excellent at explaining their decisions. The favorite is decision trees which break the decision up into discrete decisions for indi
by unishark 6y ago
By the way many methods are excellent at explaining their decisions. The favorite is decision trees which break the decision up into discrete decisions for individual features. E.g. a person was put in class 1 because their income was above X, their savings was above Y, etc. Other "shallow" methods like regression are fairly easy to interpret as well.
It is mainly deep learning for which this is difficult. Which I'm sure is the method in the twitter discussion, but that is a different kind of problem where interpretability doesn't have a clear use.
- mlyle 6y agoWhen we say "ML", we usually don't mean regression. We not mean deep learning, but at least we mean SVM, SGD, etc. They may be less inscrutable than deep learning, but can easily still draw a box around most of the black people in a clever, non-obvious way.