A Novel Data Mining Approach for Detecting Spam Emails using Robust Chi-Square Features
Mugdha Sharma, Jasmeen Kaur · 2015
In spam filtering techniques, the classification of emails are performed on the basis of a collection words that are extracted from the training set. The accuracy and performance of the classifier highly depends on features and length of feature space. Feature selection methods are used in such scenario for evaluating the best features for classification. In an attempt to develop strong spam filtering model we rank the features using Chi--Square feature ranking method and also investigate the effectiveness of feature length on classification accuracy. The results are promising and also the feature ranking method proposed is effective than other methods referred in the literature.