A Method of Spam Filtering Based on Online Linear Discriminative Learning Model
Guohua Lei · Harbin Ligong Daxue xuebao · 2008
Spam filtering is an important task in the application of internet.In this paper a method of spam filtering based on online linear discriminative Learning Model is presented.We statically derive the features using Bayesian rule,clustering them into groups according to their position and then assigning weights respectively.The model is evaluated by TREC Spam corpus and compared with the TREC results.Experimental results show that our linear discriminative model can produce competitive results.