@misc{Łęski_Jacek_M._A,
 author={Łęski, Jacek M.},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={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.},
 abstract={Next, an extension to a nonlinear classifier by the mixture-of-experts technique is presented. Each expert is represented by a fuzzy if-then rule in the Takagi-Sugeno-Kang form. Finally, examples are given to demonstrate the validity of the introduced method.},
 type={artykuł},
 title={A fuzzy if-then rule-based nonlinear classifier},
 keywords={classifier design, fuzzy if-then rules, generalization control, mixture of experts},
}