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Discriminative learning models such as Logistic Regression (LR) has shown good performance in spam filtering tasks. While most previous researches on LR have used binary features, this discards much useful information. To overcome this problem, information theory based feature valuing method for LR instead of traditional binary features is presented. The effectiveness of our approach has been evaluated...
The logistic regression model has achieved success in spam filtering. But it is disadvantaged by the equal adjustment of the feature weights appeared in both spam messages and ham ones during training period. This paper presents an improved logistic regression model which reduces the impact of the features appearing in both spam messages and ham ones. Byte level n-grams are employed to extract the...
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