An Improved E-mail Classifier Based on Support Vector Machine
Xiong Zhong · 2007
In the real spam-filtering environment,because of the complicated factor of spam itself.It’s easy to make mistakes just as the traditional support vector machine classifiers model doing-assigning an e-mail example to a class specifically.However,assigning an e-mail example to a class according to its probability output is a reasonable solution to the problem.According to the theory,we put forward an optimising idea based on the traditional SVM classification model.By computing the probability of output class,and judging the threshold of the probability,we can make sure which class the input email example belongs to.The experiment has proved that this method is efficient and feasible.