【摘要】 传统智能入侵检测模型参数的修改只能通过对训练集重新学习,从而导致模型的适应性较低,利用朴素贝叶斯模型具有增量式学习特征,通过对新训练集进行训练进而修改模型参数,从而提高模型的自适应能力.实验结果表明,模型的自适应能力得到了一定的提高.更多还原

【Abstract】 The parameter of traditional intelligent intrusion detection can not modify basis on studied model.,which will lead low of adaptiablity.By using naive bayesian feature of incremental study.We modify the parameter of model through training new train data in order to improve the adaptiability.The experiment show the adaptiability of model improve a lot.更多还原