Diagnosis on the Application of Rough Set Theory in Cheat Risks
XU Yuan-chun, Bingxiang Liu, Sheng Zhao-han · Jisuanji gongcheng · 2004
In order to compress or reduce redundant features in cheat risks diagnosis,the rough set theory is introduced and a feature reduction algorithm based on the rough set is proposed. An example in cheat risks diagnosis is given to validate the algorithm. The results show that when the cheat classification result is almost invariable,the main features which are more important to the cheat classification can be searched by this algorithm.