Fuzzy kernel covering classifier and its application
Duan Zhen · Jisuanji yingyong yanjiu · 2010
While kernel covering algorithm (KCA) is a kind of effective classification algorithm, it still falls short in treating rejection points. This paper analyzed the construction process of kernel covering algorithm. By revising the selection criteria of covering radius and introducing the membership function for rejection points, generalized the algorithm as fuzzy kernel covering algorithm (FKCA). Also discussed isolated covering’s impact on classifier’s performance and lowered the computation cost through reducing the number of coverings. Comparing with other classification methods on experiment results show this fuzzy kernel covering algorithm works well. FKCA is applied to spam filtering and the classifier’s performance is improved effectively.