Dominance-based rough set approach to knowledge discovery (ii): extensions and applications

Salvatore Greco; B. Matarazzo; R. Slowinski

doi:10.1007/978-3-662-07952-2_21

Dominance-based rough set approach to knowledge discovery (ii): extensions and applications

Salvatore Greco, B. Matarazzo, R. Slowinski

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

While the first part was devoted to the presentation of a general perspective of Dominance-based Rough Set Approach (DRSA) in the context of multicriteria classification, choice, and ranking, this part presents fuzzy set extensions of DRSA, DRSA for decisions under risk, and DRSA for hierarchical decision making. The chapter ends with a section concerning an axiomatic characterization of three preference models inferred from preference ordered data: general utility function, outranking relation, and a set of decision rules resulting from DRSA. It appears that the decision rule model is the most general among the known preference models.

Original language	English
Title of host publication	Intelligent technologies for information analysis. Vol. 4
Editors	N. Zhong, J. Liu
Place of Publication	Berlin
Publisher	Springer
Pages	553-612
Number of pages	60
ISBN (Print)	9783642073786
DOIs	https://doi.org/10.1007/978-3-662-07952-2_21
Publication status	Published - 2004

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title = "Dominance-based rough set approach to knowledge discovery (ii): extensions and applications",

abstract = "While the first part was devoted to the presentation of a general perspective of Dominance-based Rough Set Approach (DRSA) in the context of multicriteria classification, choice, and ranking, this part presents fuzzy set extensions of DRSA, DRSA for decisions under risk, and DRSA for hierarchical decision making. The chapter ends with a section concerning an axiomatic characterization of three preference models inferred from preference ordered data: general utility function, outranking relation, and a set of decision rules resulting from DRSA. It appears that the decision rule model is the most general among the known preference models.",

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AU - Matarazzo, B.

AU - Slowinski, R.

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AB - While the first part was devoted to the presentation of a general perspective of Dominance-based Rough Set Approach (DRSA) in the context of multicriteria classification, choice, and ranking, this part presents fuzzy set extensions of DRSA, DRSA for decisions under risk, and DRSA for hierarchical decision making. The chapter ends with a section concerning an axiomatic characterization of three preference models inferred from preference ordered data: general utility function, outranking relation, and a set of decision rules resulting from DRSA. It appears that the decision rule model is the most general among the known preference models.

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ER -

Dominance-based rough set approach to knowledge discovery (ii): extensions and applications

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