Impact of the Change of Training Sample Space on Bayesian Regular and Complement Class Rules Weight Estimate

In order to reduce the error rate in classification calculation of the firewall text, the operation efficiency of the Bayesian firewall test system was studied, and a new viewpoint was proposed to set Bayesian model as a linear model. To analyze the influence of test sample space changes on the different set weights rules,a MNB classifier mathematical model was set up with error compensation function. The feasibility of Bayesian s polynomial mathematical model was verified by experimental simulation,and the corresponding relationship was determined between characteristic variables of Bayesian s polynomial mathematical model in MNB classifier and character vocabulary in target text.