A novel automatic two-stage locally regularized classifier construction method using the extreme learning machine

This paper investigates the design of a linear-in-the-parameters (LITP) regression classifier for two-class problems. Most existing algorithms generally learn a classifier (model) from the available training data based on some stopping criterions, such as the Akaike's final prediction error (FP...

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