Abstract The solution based on multi-approaches of data mining involving k-means, C4.5, Nave Bayes, Bayes net and Co-training is proposed in order to deal with the major problems of intrusion detection dataset such as class balance, class overlapping, noise, distributions etc. The experiment results show its validity.
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