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Area of network traffic classification using application of machine learning has been increased enormously in recent years. Network traffic classification is necessary today because of increase in no of users today in the internet and quality of service in the network. Network traffic classification algorithm works on various network traffic features. So in a huge amount of network traffic data not every feature is relevant. So a irrelevant feature increase the time of classification algorithm. So feature selection is needed to reduce the dimensionality of feature space and reduce the computational time of classifier. In this paper, different types of features selection method are used in traffic classification are presented.
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