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Comparative study of decision performance of decision tables induced by attribute reductions

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    The given attribute reduction approach decides the decision performance of a reduced decision table, which can give a guidance for selecting one rule-extraction method in practical applications. The objective of this study is to compare the decision performance of positive-region reduction, Shannon entropy reduction and Liang entropy reduction. In this paper, the relationships between positive-region reduction, Shannon entropy reduction and Liang entropy reduction are first investigated. Then, by means of three evaluation indices (certainty measure, consistency measure and support measure), we systemically analyse these change mechanisms for decision performance of a decision table induced by each of these three types of reduction approaches. Finally, by numerical experiments, these change mechanisms of a decision table's decision performance are verified for the above-mentioned three attribute reductions. © 2010 Taylor & Francis.
    Original languageEnglish
    Pages (from-to)813-838
    JournalInternational Journal of General Systems
    Volume39
    Issue number8
    DOIs
    Publication statusPublished - Nov 2010

    Research Keywords

    • attribute reduction
    • decision performance evaluation
    • information entropy
    • rough set theory

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