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Measures of Ruleset Quality for General Rules Extraction Methods
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SYSNO ASEP 0323363 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Measures of Ruleset Quality for General Rules Extraction Methods Title Míry kvality množin pravidel pro obecné metody získávání pravidel Author(s) Holeňa, Martin (UIVT-O) SAI, RID Source Title International Journal of Approximate Reasoning. - : Elsevier - ISSN 0888-613X
Roč. 50, č. 6 (2009), s. 867-879Number of pages 13 s. Language eng - English Country US - United States Keywords rules extraction from data ; quality measures ; ruleset measures ; ROC curves ; observational logic ; fuzzy logic Subject RIV IN - Informatics, Computer Science R&D Projects GA201/08/0802 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000267232200005 EID SCOPUS 67349130842 DOI 10.1016/j.ijar.2009.03.002 Annotation The paper deals with quality measures of whole sets of rules extracted from data, as a counterpart to more commonly used measures of individual rules. It sketches the typology of rules extraction methods and of their rulesets, and recalls that quality measures for whole sets of rules have been so far used only in the case of classification rulesets. Then three particular approaches to extending ruleset quality measures from classification to general rulesets are discussed. The paper also recalls the possibility to measure the dependence of classification rulesets on parameters of the classification method by means of ROC curves, and proposes a generalization of ROC curves to general rulesets. Finally, the approach is illustrated on rulesets extracted with four important rules extraction methods from the well-known iris data. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2010
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