A bias-variance-complexity trade-off framework for complex system modeling

Authors:
Lean Yu;Kin Keung Lai;Shouyang Wang;Wei Huang
Affiliations:
Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;Department of Management Sciences, City University of Hong Kong, Kowloon, Hong Kong;Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;School of Management, Huazhong University of Science and Technology, Wuhan, China
Venue:
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
Year:
2006

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Abstract

This study proposes a new complex system modeling approach by extending a bias-variance trade-off into a bias-variance-complexity trade-off framework. In the framework, the computational complexity is introduced for system modeling. For testing purposes, complex financial system data are used for modeling. Empirical results obtained reveal that this novel approach performs well in complex system modeling and can improve the performance of complex systems by way of model ensemble within the framework.