Abstract: The correction rate and the risk rate of classification are important factors for evaluating an E-Mail system's performance,and spam filtering is a particular application of text categorization. This paper introduced covering algorithm (CA) of NN into spam filtering, and used several feature reduction methods to classify E-Mail. Comparing with SVM, the results of experiments indicated that it is an effective method to realize a spam filter using the combination of covering algorithm, appropriated feature selection and reduction methods. For the need of minimum risk of spam filtering,we proposed an improvement of one process in the handling of rejection samples by employing cross cover algorithm according to the result of analysis. The results show that this method can reduce the risk by changing the area which is affected by normal mail.

Key words: Spam filtering, Covering algorithm, Feature selection, Feature reduction