Abstract—In the paper, information table for network traffic data is discretized by supervised learning using WEKA and from this discretized data, three different algorithms for calculation of rules are applied, genetic algorithm, covering algorithm and LEM2 algorithm. Rough set classification through three different table rule set are done and accuracies are observed. It has been concluded that out of these three methods of rule calculation, classification through table rule set using covering algorithm yields best accuracy. In fourth table of classification, rules have been calculated through reduct generation but in that case, rough set classification produces same total accuracy of classification through covering algorithm. RSES software is used for rule set calculation, reduct generation and rough set classification.
Index Terms—Classification, network traffic, reducts, rough set theory, rule generation.
N. Sengupta is with University College of Bahrain, P O Box 55040,Manama, Bahrain (e-mail: firstname.lastname@example.org)
J. Sil is with Bengal Engineering and Science University Shibpur, P O Botanic Garden, Howrah, West Bengal, Pin 711103 (e-mail: email@example.com).
Cite: Nandita Sengupta and Jaya Sil, "Comparison of Different Rule Calculation Method for Rough Set Theory," International Journal of Information and Electronics Engineering vol. 2, no. 3, pp. 464-466, 2012.