A multi-factorial decision-making model for deduction of rules in rough sets

Author

Junsheng, Wang ; MinQiang, Li

Author_Institution

Dept. of Manage. Inf. Syst., Tianjin Univ., China

Volume

1

fYear

2000

fDate

2000

Firstpage

383

Abstract

Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. It has been used in machine learning, knowledge discovery, decision support systems and pattern recognition. Traditionally, the algorithm to obtain the deduction of decision rule in rough sets theory always take into account the number of decision rules more than their cost. In this paper, we introduce how to reconcile the conflict of the simplicity and the cost of rules by using multiple objective decision-making (MOD), and the efficiency and effectiveness of rough set can be improved

Keywords

data mining; decision support systems; decision theory; learning (artificial intelligence); rough set theory; uncertain systems; DSS; MOD; decision rule deduction; decision support systems; knowledge discovery; machine learning; multifactorial decision-making model; multiple objective decision-making; pattern recognition; rough set theory; uncertainty; vagueness; Costs; Decision making; Decision support systems; Machine learning; Machine learning algorithms; Management information systems; Pattern recognition; Rough sets; Set theory; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.859988

Filename

859988