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Traffic classification in computer networks has very significant roles in network operation, management, and security. Examples include controlling the flow of information, allocating resources effectively, provisioning quality of service, detecting intrusions, and blocking malicious and unauthorized access. This problem has attracted a growing attention over years and a number of techniques have...
This paper introduces new techniques for learning the classification method PROAFTN from data. PROAFTN is a multi-criteria classification method and belongs to the class of supervised learning algorithms. To use PROAFTN for classification, some parameters must be obtained for this purpose. Therefore, an automatic method to extract these parameters from data with minimum classification errors is required...
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