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Development of Automatic Rule Extraction Method in Data Mining : An Approach based on Hierarchical Clustering Algorithm and Rough Set Theory
Journal of The Korea Society of Computer and Information
Abbr :
JKSCI
2009, 14(6), pp.135-142
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
2009, 14(6), pp.135-142
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science
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Data mining is an emerging area of computational intelligence that offers new theories, techniques, and tools for analysis of large data sets. The major techniques used in data mining are mining association rules, classification and clustering. Since these techniques are used individually, it is necessary to develop the methodology for rule extraction using a process of integrating these techniques. Rule extraction techniques assist humans in analyzing of large data sets and to turn the meaningful information contained in the data sets into successful decision making. This paper proposes an autonomous method of rule extraction using clustering and rough set theory. The experiments are carried out on data sets of UCI KDD archive and present decision rules from the proposed method. These rules can be successfully used for making decisions.
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