2 (解放军炮兵学院三 系 合 肥 230031) A Classification Approach Based on Evolutionary Neural Networks

Abstract

Abstract: Classification is important in data mining and machine learning. In this paper, a classification approach based on evolutionary neural networks(CABEN) is presented, which establishes classifiers by a group of three-layer feed-forward neural networks. We train the neural networks by means of an improving algorithm synthesizing modified Evolutionary Strategy and Levenberg-Marquardt optimized method. The class label of the identifying data can first be evaluated by each neural network, and the final classification result is obtained according to the absolute-majority-voting rule. Experimental results show that the algorithm CABEN is effective for the classification, and has the better performance comparing with the traditional neural network methods, Bayesian classifiers and decision trees, especially for the complex classification problems with many classes