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An alternative is to use machine learning (ML) techniques and identify network applications based on per-flow statistics, derived from payload-independent features such as packet length and inter-arrival time distributions. The performance impact of feature set reduction, using Consistency-based and Correlation-based feature selection, is demonstrated on Na\u00efve Bayes, C4.5, Bayesian Network and Na\u00efve Bayes Tree algorithms. 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