A Classification Method by Using Fuzzy Neural Network and Ensemble Learning

Abstract

In this paper, a new multi-class classification technology combining fuzzy neural network and ensemble learning technology is proposed. Several fuzzy neural networks, including fuzzy TS neural network and fuzzy wavelet neural network, are considered as sub-classifiers. Restricted Boltzmann machines and gradient descent algorithm are used to train the parameters of fuzzy neural network. Then, adaptive boosting (AdaBoost) algorithm based on hypothesis margin and particle swarm optimization is provided to determine the weights of sub-classifiers. Numerical simulation results illustrate the validity of proposed method.