Anti-spam model based on semi-Naive Bayesian classification model
Yue Wu · Journal of Computer Applications · 2009
Because Naive Bayes(NB) classification model is simple and effective,good efficiency can be achieved in anti-spam applications.On the other hand,the assumption of its attribute independence makes it unable to express its semantic dependence.This paper proposed a new anti-spam classification model based on semi-NB classification model,averaged on N one-dependence classification model.It relaxed the assumption of condition independence of each attribute.It was assumed that all attributes were dependent on one attribute(1-dependence).The average on N 1-dependence was regarded as the probability of each class label.This method is simple and efficient and decreases the classification error ratio.