A Bayesian Classification Algorithm Based-on One-Class SVM

A Bayesian classification algorithm based on one-class SVM is presented.It constructs the Bayesian classifier using the classes' conditional density estimated by one-class SVM.It is proven that the solution of one-class SVM using the Gaussian kernel can be normalized as an estimate of probability density,and can be used to obtain the Bayesian classifier.Experimental results showed that the proposed classifier outperformed NaiveBayes and BayesNet in terms of prediction accuracy,comparable to traditional two-class SVM.The size of kernel matrix of the new algorithm is less than that of the traditional two-class SVM,which lead to less training time for the new classifier.