The Discretization Algorithm Based on Rough Set and its Application

Zhi Cai Shi; Yong Xiang Xia; Chao Gang Yu; Jin Zu Zhou

doi:10.4028/www.scientific.net/AMM.416-417.1399

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 416-417The Discretization Algorithm Based on Rough Set...

The Discretization Algorithm Based on Rough Set and its Application

Abstract:

The discretization is one of the most important steps for the application of Rough set theory. In this paper, we analyzed the shortcomings of the current relative works. Then we proposed a novel discretization algorithm based on information loss and gave its mathematical description. This algorithm used information loss as the measure so as to reduce the loss of the information entropy during discretizating. The algorithm was applied to different samples with the same attributes from KDDcup99 and intrusion detection systems. The experimental results show that this algorithm is sensitive to the samples only for parts of all attributes. But it dose not compromise the effect of intrusion detection and it improves the response performance of intrusion detection remarkably.

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Periodical:

Applied Mechanics and Materials (Volumes 416-417)

Pages:

1399-1403

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.416-417.1399

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Online since:

September 2013

Authors:

Zhi Cai Shi, Yong Xiang Xia, Chao Gang Yu, Jin Zu Zhou

Keywords:

Discretization, Entropy, Information Loss, Rough Set (RS)

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References

[1] Z Paw lak: Rough Set Theory and Its Application to Data Analysis. Cybernetics and Systems, Vol. 29 (1998), pp.661-688.

Google Scholar

[2] Xie Hong, Cheng Haozhong: The Discretization Algorithm Based on Entropy for the Continuous Attributes on Rough Set. Chinese Journal of Computer, Vol. 28 (2005), pp.1570-1574.

Google Scholar

[3] U. Fayyad, K. Irani: Multi-interval Discretization of Continuous-valued Attributes for Classification Learning. Proc. of the 13th International Joint Conference on Artificial Intelligence. Morgan Kaufmann Publisher, pp.1022-1027. (1993).

Google Scholar

[4] R. C. Kerber: Discretization of Numeric Attributes. Proceedings of the 10th National Conference on Artificial Intelligence. MIT Press, pp.123-128. (1992).

Google Scholar

[5] KDDcup99-Dataset on http: /kdd. ics. uci. edu/databases/ kddcup99/ task. html.

Google Scholar

[6] Zhao Xibin, Jing Ranzhe: Adaptive Intrusion Detection Algorithm Based on Rough Set. Chinese Journal of Qinghua University, Vol. 48 (2008), pp.1165-1168.

Google Scholar

[7] Xia Yongxiang, Shi Zhicai: An Incremental SVM for Intrusion Detection Based on Key Feature Selection. Proc. of the Third International Symposium on Intelligent Information Technology Application, IEEE Press, pp.205-208. (2009).

DOI: 10.1109/iita.2009.358

Google Scholar