Rough set-based approach to rule generation and rule induction |
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Authors: | Jia-yuarn Guo Vira Chankong |
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Affiliation: | Electrical Engineering and Computer Science , Case Western Reserve University , OH, 44106-1712, USA |
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Abstract: | During the last decade, databases have been growing rapidly in size and number as a result of rapid advances in database capacity and management techniques. This expansive growth in data and databases has caused a pressing need for the development of more powerful techniques to convert the vast pool of data into valuable information. For the purpose of strategic and decision-making, many companies and researchers have recognized mining useful information and knowledge from large databases as a key research topic and as an opportunity for major revenues and improving competitiveness. In this paper, we will explore a new rule generation algorithm (based on rough sets theory) that can generate a minimal set of rule reducts, and a rule generation and rule induction program (RGRIP) which can efficiently induce decision rules from conflicting information systems. All the methods will also be illustrated with numerical examples. |
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Keywords: | Rough Sets Decision Rules Rule Induction Classification |
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