In this article, we offer a method to successfully enhance a traffic classifier based on Naive Bayes Prediction with a limited collection of training samples. Here, you should put forth a fresh traffic classification strategy to make use of data from correlated traffic patterns produced by an application. Traffic patterns are represented by statistical characteristics that are extracted. To implement Correlation based feature selection to eliminate pointless and superfluous features from the feature collection with low intercorrelation and high class-specific correlation. The classification ability of different traffic classification methods can be successfully demonstrated by Naive Bayes prediction. In comparison with current state-of-the-art traffic classification methods, suggested strategycan produce significantly improved classification results. Getting a high-performance analytic characteristic is one of the system's goals.

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