Lazy Learning Spam Filtering Model Based on Embedded Feature Selection
Xiao Yun-hong · Journal of Chinese Computer Systems · 2009
Although being more suitable than Eager Learning Text Categorization Approaches for spam filtering,Lazy Learning approaches are generally in lower efficiency.Moreover,they always need Feature Selection process to reduce dimensionality of feature space.This process will cause information losing to have side-effect on the whole performance of approaches.So the paper issued a new spam filtering model based on Embedded Feature Selection Mode,which can reduce dimensionality of feature space greatly without any information losing,the approach based on this model thus can improve both efficiency and performance greatly.