Attribute Reduction Algorithm on Balancing Profit and Risk

Authors

Dexing Wang, College of Information Technology, Shanghai Ocean University, Shanghai 201306, China;
Jielong Xu, College of Information Technology, Shanghai Ocean University, Shanghai 201306, China;
Hongchun Yuan, College of Information Technology, Shanghai Ocean University, Shanghai 201306, China;

Abstract

Abstract: Usually it is taken for granted to achieve the maximal profit at the cost of the minimal risk. It is an important problem of how to balance profit and risk, considering introducing profit and risk to attribute reduction so as to find practical algorithms in decision-making process. A decision-theoretic model was built, which could balance profit and risk combining with decision-theoretic rough set model and minimum risk of Bayes decision and find optimal combinations of risk in a certain level of expected profit, then a heuristic algorithm of attribute reduction was proposed, which took the function of balancing profit and risk as the target of heuristic attribute reduction, and it could reduce the scales and complexity of data model, and then improve the simulation precision of the model system.

Recommended Citation

Wang, Dexing; Xu, Jielong; and Yuan, Hongchun (2020) "Attribute Reduction Algorithm on Balancing Profit and Risk," Journal of System Simulation: Vol. 27: Iss. 2, Article 20.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss2/20

First Page

369

Revised Date

2014-09-23

DOI Link

https://doi.org/

Last Page

375

CLC

TP301.6

Recommended Citation

Wang Dexing, Xu Jielong, Yuan Hongchun. Attribute Reduction Algorithm on Balancing Profit and Risk[J]. Journal of System Simulation, 2015, 27(2): 369-375.