A fuzzy if-then rule-based nonlinear classifier - Łęski, Jacek M. (Zielona Góra: Uniwersytet Zielonogórski)
This paper introduces a new classifier design method that is based on a modification of the classical Ho-Kashyap procedure. The proposed method uses the absolute error, rather than the squared error, to design a linear classifier. Additionally, easy control of the generalization ability and robustness to outliers are obtained.
Keywords: classifier design; fuzzy if-then rules; generalization control; mixture of experts