This paper presentes a new hybrid classifier based on the combination of rough set theory and RBF neural network. Experimental results show that the algorithm Rough-RBF is effective for the texts classification, and has the better performance in classification precision, stability and fault-tolerance comparing with the traditional classification methods, Bayesian classifiers SVM and kNN, especially for the complex classification problems with many feature vectors.
白如江 . 基于粗糙集和RBF神经网络的文本自动分类方法[J]. 现代图书情报技术, 2006, 1(6): 47-51.
Bai Rujiang . A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks. New Technology of Library and Information Service, 2006, 1(6): 47-51.
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