Problems that are characterized by unsharp specified knowledge but can be described by a sufficient number of samples in training sets are likely to be best classified by artificial neural networks.
Decision instances could additionally exploit the benefits of unsharp "fuzzy" logic.
But don't worry: "nothing is fuzzy about fuzzy logic!"
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