A Selective Augmented Naive Bayesian Classifier Based on MDL Score
Mengran Zhou · Computer Technology and Development · 2007
Naive Bayesian classifier is a simple and effective classifier,but its conditional independence assumption makes it unable to express the dependence among features.TAN classifier extends the structure of Naive Bayes classifier by adding augmenting arcs that obey certain structural restrictions.In TAN classifier,all features are constrained to have the class variable as a parent,but some features degrade its classification accuracy.The present paper presents SANC(A Selective Augmented Naive Bayesian Classifier based on MDL score) that removes features and augmenting arcs which affect the performance of classification by MDL score.Compared with NBC and TANC,experimental results show SANC has higher accuracy.