Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system

• Main Authors: Noor Suhana, Sulaiman, Rohani, Abu Bakar
• Format: Article
• Language: English
• Published: Digital Information Research Foundation, India 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/21203/1/Rough%20Set%20Discretization%20Equal%20Frequency%20Binning%2C%20Entropy%20MDL%20and%20Semi%20Naives.pdf; http://umpir.ump.edu.my/id/eprint/21203/; http://www.dline.info/jic/fulltext/v8n3/jicv8n3_2.pdf
• Institution: Universiti Malaysia Pahang

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.