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Spam Filtering Based on Improved CHI Feature Selection Method

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4 Author(s)
Zhimao Lu ; Pattern Recognition & Natural Comput. Lab., Harbin Eng. Univ., Harbin, China ; Hongxia Yu ; Dongmei Fan ; Chaoyue Yuan

In this paper, methods of feature selection used in the spam filtering are studied, including CHI square (CHI), Expected Cross Entropy (ECE), the Weight of Evidence for Text (WET) and Information Gain (IG) and a novel modified CHI feature selection method is proposed in spam filtering. The spam filter combined Support Vector Machine (SVM) is selected to evaluate the CHI square, Expected Cross Entropy, the Weight of Evidence for Text, Information Gain and modified CHI. The experiment proved that the modified CHI could improve the precision, recall and F test measure of spam filter and the modified CHI feature selection method is effective.

Published in:

Pattern Recognition, 2009. CCPR 2009. Chinese Conference on

Date of Conference:

4-6 Nov. 2009

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