An Enhanced Swarm Intelligence Clustering-Based RBF Neural Network Web Text Classifier

Authors:
Yong Feng;Zhongfu Wu;Jiang Zhong;Chunxiao Ye;Kaigui Wu
Affiliations:
College of Computer Science, Chongqing University, Chongqing, China 400030;College of Computer Science, Chongqing University, Chongqing, China 400030;College of Computer Science, Chongqing University, Chongqing, China 400030;College of Computer Science, Chongqing University, Chongqing, China 400030;College of Computer Science, Chongqing University, Chongqing, China 400030
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

The central problem in training a radial basis function neural network (RBFNN) is the selection of hidden layer neurons, which includes the selection of the center and width of those neurons. In this paper, we propose an enhanced swarm intelligence clustering (ESIC) method to select hidden layer neurons, and then, training a cosine RBFNN base on gradient descent learning process. Also, the new method is applied for web text classification. Experimental results show that the average Accuracy, Precision and Recall of our ESIC-based RBFNN classifier maintained a better performance than BP, SVM and OLS RBF.