Spam Filtering System Based on Rough Set and Naive Bayes
Shaobo Deng · Journal of Nanchang University · 2009
This paper proposed a spam filtering method based on Rough set theory and Bayesian classifier algorithm.Then the amount of features are reduced by deleting redundant features with little significance on filtering effect based on rough set theory,resulting in a input sample with reduced number of dimension.Using this method,it can overcome the shortages of Bayies classifier-time-consuming of training and massive dataset storage.Experiments proved that this mechanism could greatly boost both the system's accuracy and the training speed.