Adaptive Intrusion Detection based on Boosting and Naïve Bayesian Classifier
نویسندگان
چکیده
In this paper, we introduce a new learning algorithm for adaptive intrusion detection using boosting and naïve Bayesian classifier, which considers a series of classifiers and combines the votes of each individual classifier for classifying an unknown or known example. The proposed algorithm generates the probability set for each round using naïve Bayesian classifier and updates the weights of training examples based on the misclassification error rate that produced
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