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New Technology of Library and Information Service  2006, Vol. 1 Issue (6): 47-51    DOI: 10.11925/infotech.1003-3513.2006.06.12
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A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks
Bai Rujiang
(Library of Shandong University of Technology, Zibo 255049,China)
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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.

Key wordsText classification      Rough-sets      Neural network      Attribute reduction      VSM     
Received: 21 March 2006      Published: 25 June 2006


Corresponding Authors: Bai Rujiang     E-mail:
About author:: Bai Rujiang

Cite this article:

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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