四川大学学报（自然科学版）2012，Vol.49Issue(6)：1235-1239,5.DOI:10.3969/j.issn.0490-6756.2012.06.012
基于改进的模糊聚类RBF网络集成的文本分类方法
Text classification based on improved Fuzzy clustering RBF neural network ensemble
摘要
Abstract
Web text classification is a hot issue in the research on data mining. In view of the characteristics of high dimension text vector, the paper proposes an improved text classification method of fuzzy cluster RBF network integration. The method uses fuzzy c-means clustering algorithm to simplify and extract the text eigenvector, introduces adaptive genetic algorithm for optimization of RBF Neural network weights, and builds a RBF network model for text classification. Experimental results show that the method possesses a higher classification efficiency and accuracy.关键词
RBF神经网络/文本分类/模糊聚类/神经网络集成/自适应遗传算法Key words
RBF neural network,text classification, fuzzy clustering,adaptive genetic algorithm分类
信息技术与安全科学引用本文复制引用
张爱科,符保龙,李辉..基于改进的模糊聚类RBF网络集成的文本分类方法[J].四川大学学报（自然科学版）,2012,49(6):1235-1239,5.基金项目
广西教育厅科研项目(200911LX486,201106LX745,201204LX593) （200911LX486,201106LX745,201204LX593）
