Spam Filter Based on Multiple Classifier Combinational Model
Congfu Xu · Jisuanji gongcheng · 2010
Aiming at the unequal cost problem of spam filter that the cost of ham misclassification is much more than the cost of spam misclassification,this paper proposes a combinational classifier with two-layer structure.Email samples are pre-processed.The filter combines the behavioral features and text features,and optimizes the combination of different classifiers based on improving the performance of a single one.The classifier adjusts the model by timely feedback to make the filter obtain efficient self-learning function.