Theorem: [Lippmann, Richard]
If we reach the global minimum using targets and the right MLP architecture, we are guaranteed that the MLP obtained this way is the optimal Bayesian Classifier, as long as the class-posteriors are continuous.
In practice, using backpropagation on real world data we will never find the global minimum.
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