Applying RBF Network to Web Classification Mining
نویسندگان
چکیده
To effectively organize and analyze massive Web information, in this paper, we have designed a Web classification mining system. BP network has lots of disadvantages, so we have proposed a method that uses RBFNN (Radial Basis Function Neural Network) to classify the text information in Web pages. In this paper, the model of classification system mainly includes RBF (Radial Basis Function) classifier, estimate model and data pretreatment. Using Macro-Fi as standard of estimate of classification performance, experimental results can verify that RBFNN classification has better classification accuracy and is more efficient than BPNN algorithm. We also analyze the results of different classification accuracy, using the same classifier to classify different classes.
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