An Empirical Evaluation of the Fuzzy Kernel Perceptron
Gavin C. Cawley · IEEE Transactions on Neural Networks · 2007
J.-H. Chen and C.-S. Chen have recently proposed a nonlinear variant of Keller and Hunt's fuzzy perceptron algorithm, based on the now familiar "kernel trick." In this letter, we demonstrate experimentally that J.-H. Chen and C.-S. Chen's assertion that the fuzzy kernel perceptron (FKP) outperforms the support vector machine (SVM) cannot be sustained. A more thorough model comparison exercise, based on a much wider range of benchmark data sets, shows that the FKP algorithm is not competitive with the SVM.