Machine Learning Classifier for Internet Traffic from Academic Perspective

作者: S Agrawal , Jaspreet Kaur , BS Sohi

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摘要: The infinite number of websites in the internet world can be classified into different categories ways. But if we talk about educational institutions, two categories, and non-educational websites. Educational are those which used by students to acquire knowledge, explore topics, for research work etc. noneducational entertainment keep touch with people get know more people. In institutes optimum use network resources welfare students, should banned while only allowed access. Recent trends ML (machine learning) algorithms traffic classification. this paper, three classifiers Bayes Net, C4.5 Radial basis function (RBF) neural classify compare their performances. Results show that Net gives best performance intended classification terms accuracy, training time classifiers, recall precision.

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