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Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System

Noor Suhana, Sulaiman and Rohani, Abu Bakar (2016) Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System. In: Advances in Digital Technologies: Proceedings of the 7th International Conference on Applications of Digital Information and Web Technologies 2016. Frontiers in Artificial Intelligence and Applications, 282 . IOS Press, Amsterdam, pp. 77-87. ISBN 978-1-61499-636-1 (print); 978-1-61499-637-8 (online)

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Abstract

Discretization of real value attributes is a vital task in data mining, particularly in the classification problem. Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. Universally, discretization is a process of searching for partition of attribute domains into intervals and unifying the values over each interval. Significant discretization technique suit to the Intrusion Detection System (IDS) data need to determine in IDS framework, since IDS data consist of huge records that need to be examined in system. There are many Rough Set discretization technique that can be used, among of them are Semi Naives and Equal Frequency Binning.

Item Type: Book Section
Uncontrolled Keywords: Rough set; Semi naives; Equal Frequency Binning; Intrusion Detection System
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Ms. Hazima Anuar
Date Deposited: 17 Jun 2016 01:05
Last Modified: 22 May 2018 03:16
URI: http://umpir.ump.edu.my/id/eprint/6811
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