Multilevel spam filter based on correlation
Dihua Xu · Jisuanji yingyong yanjiu · 2010
A group tasks learning simultaneously may have better generalization ability than learning individually,inspired by which,this paper proposed a multilevel spam filter based on correlation coefficient. The system used EM algorithm to estimates the correlation coefficient,by which the system got a spam discriminant. Experiments show that the system is reliable and effective for both Chinese and English corpus. It can get good performance even if given small sample set. The performance of the system ultimately depends on the parameters value of the priori of the correlation coefficient,and the choice of base classifiers.