Using Genetic Rule-Based Classifier System for Data Mining


Myung-Mook Han, Journal of Information Processing Systems Vol. 1, No. 1, pp. 63-72, Nov. 2000  


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Abstract

Data mining means a process of nontrivial extraction of hidden knowledge or potentially useful information from data in large databases. Data mining algorithm is a multi-disciplinary field of research; machine learning, statistics, and computer science all make a contribution. Different classification schemes can be used to categorize data mining methods based on the kinds of tasks to be implemented and the kinds of application classes to be utilized, and classification has been identified as an important task in the emerging field of data mining. Since classification is the basic element of human's way of thinking, it is a well-studied problem in a wide varietyof application. In this paper, we propose a classifier system based on genetic algorithm with robust property, and the proposed system is evaluated by applying it to nDmC problem related to classification task in data mining.


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Cite this article
[APA Style]
Han, M. (2000). Using Genetic Rule-Based Classifier System for Data Mining. Journal of Internet Computing and Services, 1(1), 63-72.

[IEEE Style]
M. Han, "Using Genetic Rule-Based Classifier System for Data Mining," Journal of Internet Computing and Services, vol. 1, no. 1, pp. 63-72, 2000.

[ACM Style]
Myung-Mook Han. 2000. Using Genetic Rule-Based Classifier System for Data Mining. Journal of Internet Computing and Services, 1, 1, (2000), 63-72.