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- W2152319606 abstract "A new method is proposed for two pattern classification and feature extraction based directly on an optimum decision boundary using neural networks (NN). The proposed approach has several desirable properties: (1) it predicts an optimum decision boundary which provides a classification accuracy at least as good as as that of an optimum global decision hyperplane; (2) it extracts optimum discrimination features even though the joint probability distribution of features is unknown; and (3) it determines the minimum number of discriminating features. >" @default.
- W2152319606 created "2016-06-24" @default.
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- W2152319606 date "2002-12-17" @default.
- W2152319606 modified "2023-10-01" @default.
- W2152319606 title "Two-pattern classification and feature extraction based on minimum error decision boundary using neural networks" @default.
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- W2152319606 doi "https://doi.org/10.1109/isit.1994.394799" @default.
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