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This paper focuses on how to use class-modular single-hidden-layer perceptrons (MLPs) with sigmoid activation functions (SAFs) to solve the multi-class learning problems, and pays special attention to the unbalanced data sets. Our solutions are as follows. (A) An n-class learning problem first decomposes into n two-class problems (B) A single-output MLP is responsible for solving a two-class problem,...