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In this paper, we propose a novel rough set based algorithm to induce decision trees. To improve the computation efficiency of our algorithm, the rough set based attribute reduction technology is used to filter out the irrelevant attributes from the original set of attributes. And the notions of the significance of attribute and the uniformity of attribute in rough sets are adopted as the heuristic information for the selection of splitting attributes. Moreover, we apply the proposed algorithm to intrusion detection. The experimental results demonstrate that our algorithm can provide competitive solutions efficiently.

A Rough Set Based Decision Tree Algorithm and Its Application in Intrusion Detection