Taxonomy of Machine Learning Algorithms to classify real- time Interactive applications

نویسندگان

  • Hamza Awad
  • Hamza Ibrahim
  • Sulaiman Mohd Nor
  • Aliyu Mohammed
چکیده

the needs of Internet applications QoS guarantee increased the demand of internet traffic classification, especially for interactive real time applications. Therefore, several classification methods were developed. Machine Learning (ML) classification is one of the most modern techniques, which solves the problem of traditional port base method. This paper compared experimentally the accuracy of ten ML algorithms, that when it’s used to classify interactive applications. The technique applied by collecting of real data from UTM. The result shows that Tree.RandomForest algorithm provided optimal results of 99.8% accuracy, compared with other algorithms. Keywords-Classification; Mashine Learning; Interactive application;

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تاریخ انتشار 2012