Paper Info
Title
Automatic feature weighting for improving financial Decision Support Systems.
Abstract
We propose a novel methodology for improving financial Decision Support Systems (DSS) through automatic feature weighting. Using this methodology, we show that automatic feature weighting leads to a significant improvement in the performance of decision-making algorithms over financial data, which are the key of financial DSS. The statistical analysis carried out shows that metaheuristic algorithms are good for automatic feature weighting, and that Differential Evolution (DE) offers a good trade-off between decision-making performance and computational cost. We believe these results contribute to the development of novel financial DSS.
Year
DOI
Venue
2018
10.1016/j.dss.2018.01.005
Decision Support Systems
Keywords
Field
DocType
Credit risk,Bankruptcy prediction,Banknote authentication,Bank telemarketing,Feature weight,Decision support
Data mining,Weighting,Computer science,Decision support system,Differential evolution,Finance,Metaheuristic,Statistical analysis
Journal
Volume
Issue
ISSN
107
C
0167-9236
Citations 
PageRank 
References 
3
0.37
15
Authors
3
Name
Order
Citations
PageRank
Yosimar O. Serrano-Silva130.37
Yenny Villuendas-rey24614.38
Cornelio Yanez Marquez3172.99