Bayesian decision theory for dominance-based rough set approach

Salvatore Greco; R. Slowinski; Y. Yao

doi:10.1007/978-3-540-72458-2_16

Bayesian decision theory for dominance-based rough set approach

Salvatore Greco, R. Slowinski, Y. Yao

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

Abstract

Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., "the larger the mass and the smaller the distance, the larger the gravity", or "the more a tomato is red, the more it is ripe". These monotonicity relationships are fundamental in rough set approach to multiple criteria decision analysis. In this paper, we propose a Bayesian decision procedure for DRSA. Our approach permits to take into account costs of misclassification in fixing parameters of the Variable Consistency DRSA (VC-DRSA), being a probabilistic model of DRSA.

Original language	English
Title of host publication	Rough sets and knowledge technology: proceedings of the second international conference
Editors	J. Yao, P. Lingras, W. Wu, M. Szczuka, N. Cercone, D. Slezak
Place of Publication	Berlin
Publisher	Springer
Pages	134-141
Number of pages	8
Volume	4481
Edition	4481
ISBN (Print)	9783540724575
DOIs	https://doi.org/10.1007/978-3-540-72458-2_16
Publication status	Published - 2007

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Number	4481

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10.1007/978-3-540-72458-2_16

http://link.springer.com/chapter/10.1007%2F978-3-540-72458-2_16

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Greco, S., Slowinski, R., & Yao, Y. (2007). Bayesian decision theory for dominance-based rough set approach. In J. Yao, P. Lingras, W. Wu, M. Szczuka, N. Cercone, & D. Slezak (Eds.), Rough sets and knowledge technology: proceedings of the second international conference (4481 ed., Vol. 4481, pp. 134-141). (Lecture notes in computer science; No. 4481). Springer. https://doi.org/10.1007/978-3-540-72458-2_16

Greco, Salvatore ; Slowinski, R. ; Yao, Y. / Bayesian decision theory for dominance-based rough set approach. Rough sets and knowledge technology: proceedings of the second international conference. editor / J. Yao ; P. Lingras ; W. Wu ; M. Szczuka ; N. Cercone ; D. Slezak. Vol. 4481 4481. ed. Berlin : Springer, 2007. pp. 134-141 (Lecture notes in computer science; 4481).

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abstract = "Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., {"}the larger the mass and the smaller the distance, the larger the gravity{"}, or {"}the more a tomato is red, the more it is ripe{"}. These monotonicity relationships are fundamental in rough set approach to multiple criteria decision analysis. In this paper, we propose a Bayesian decision procedure for DRSA. Our approach permits to take into account costs of misclassification in fixing parameters of the Variable Consistency DRSA (VC-DRSA), being a probabilistic model of DRSA.",

author = "Salvatore Greco and R. Slowinski and Y. Yao",

year = "2007",

doi = "10.1007/978-3-540-72458-2_16",

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volume = "4481",

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number = "4481",

pages = "134--141",

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booktitle = "Rough sets and knowledge technology: proceedings of the second international conference",

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Greco, S, Slowinski, R & Yao, Y 2007, Bayesian decision theory for dominance-based rough set approach. in J Yao, P Lingras, W Wu, M Szczuka, N Cercone & D Slezak (eds), Rough sets and knowledge technology: proceedings of the second international conference. 4481 edn, vol. 4481, Lecture notes in computer science, no. 4481, Springer, Berlin, pp. 134-141. https://doi.org/10.1007/978-3-540-72458-2_16

Bayesian decision theory for dominance-based rough set approach. / Greco, Salvatore; Slowinski, R.; Yao, Y.
Rough sets and knowledge technology: proceedings of the second international conference. ed. / J. Yao; P. Lingras; W. Wu; M. Szczuka; N. Cercone; D. Slezak. Vol. 4481 4481. ed. Berlin: Springer, 2007. p. 134-141 (Lecture notes in computer science; No. 4481).

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

TY - CHAP

T1 - Bayesian decision theory for dominance-based rough set approach

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AU - Slowinski, R.

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AB - Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., "the larger the mass and the smaller the distance, the larger the gravity", or "the more a tomato is red, the more it is ripe". These monotonicity relationships are fundamental in rough set approach to multiple criteria decision analysis. In this paper, we propose a Bayesian decision procedure for DRSA. Our approach permits to take into account costs of misclassification in fixing parameters of the Variable Consistency DRSA (VC-DRSA), being a probabilistic model of DRSA.

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DO - 10.1007/978-3-540-72458-2_16

M3 - Chapter (peer-reviewed)

SN - 9783540724575

VL - 4481

T3 - Lecture notes in computer science

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BT - Rough sets and knowledge technology: proceedings of the second international conference

A2 - Yao, J.

A2 - Lingras, P.

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A2 - Szczuka, M.

A2 - Cercone, N.

A2 - Slezak, D.

PB - Springer

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Greco S, Slowinski R, Yao Y. Bayesian decision theory for dominance-based rough set approach. In Yao J, Lingras P, Wu W, Szczuka M, Cercone N, Slezak D, editors, Rough sets and knowledge technology: proceedings of the second international conference. 4481 ed. Vol. 4481. Berlin: Springer. 2007. p. 134-141. (Lecture notes in computer science; 4481). doi: 10.1007/978-3-540-72458-2_16

Bayesian decision theory for dominance-based rough set approach

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