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We propose a new class of neurofuzzy construction algorithms with the aim of maximizing generalization capability specifically for imbalanced data classification problems based on leave-one-out (LOO) cross-validation. The algorithms are in two stages: First, an initial rule base is constructed based on estimating the Gaussian mixture model with analysis of variance decomposition from input data; the...
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