A framework for similarity-based classification methods
نویسنده
چکیده
A general framework for similarity-based (SB) classification methods is presented. Neural networks, such as the Radial Basis Function (RBF) and the Multilayer Perceptrons (MLPs) models, are special cases of SB methods. Many new versions of minimal distance methods are derived from this framework.
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