Packet Classification Using Improved Random Forest Algorithm

Author:

Sonai Veeramani,Bharathi Indira

Publisher

Springer Nature Switzerland

Reference22 articles.

1. Amaral, P., Dinis, J., Pinto, P., Bernardo, L., Tavares, J., Mamede, H.S.: Machine learning in software defined networks: data collection and traffic classification. In: 2016 IEEE 24th International Conference on Network Protocols (ICNP) (2016)

2. Ashari, A., Paryudi, I., Min Tjoa, A.: Performance comparison between Naïve Bayes, decision tree and k-nearest neighbor in searching alternative design in an energy simulation tool. Int. J. Adv. Comput. Sci. Appl. 4(11), pp. 33–39 (2013)

3. Bharathi, I., Krishnasamy, V., Sonai, V.: GA based adaptive learning algorithm for IPv4 packet classification. Des. Eng. 21, 3236–3256 (2021)

4. Biau, G.: Analysis of a random forests model. J. Mach. Learn. Res. 13(1), 1063–1095 (2012)

5. Choudhury, M.R., Muraleedharan, N., Acharjee, P., George, A.T.: Network traffic classification using supervised learning algorithms. In: 2023 International Conference on Computer, Electrical & Communication Engineering (ICCECE), pp. 1–6 (2023)

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