The Research of the Chinese Spam Filtering Feature Selection Method by Multi-feature Combination
Zhao Junshen · 2013
In Chinese spam filtering system,Naive Bayes algorithm based on content filtering has been widely used. The combination of characteristics to build the e- mail text vector by eight text classification feature selection method is applied to Naive Bayes algorithm for experimental verification. The performance evaluation results show that six feature selection methods,category distinguish words,odds ratio,information gain,expected cross entropy,CHI statistical and textual evidence weight,is made good spam filtering performance to the multi- feature combined with the text vector filtering by the comprehensive performance indicator F1 value of precision and recall rate,and anti- spam effect is good.