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Elite bases regression: A real-time algorithm for symbolic regression
Chen C(陈辰)1,2; Luo ZT(罗长童)1; Jiang ZL(姜宗林)1,2
Source PublicationICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
Conference Name13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017
Conference DateJuly 29, 2017 - July 31, 2017
Conference PlaceGuilin, Guangxi, China
AbstractSymbolic regression is an important but challenging research topic in data mining. It can detect the underlying mathematical models. Genetic programming (GP) is one of the most popular methods for symbolic regression. However, its convergence speed might be too slow for large scale problems with a large number of variables. This drawback has become a bottleneck in practical applications. In this paper, a new non-evolutionary real-time algorithm for symbolic regression, Elite Bases Regression (EBR), is proposed. EBR generates a set of candidate basis functions coded with parse-matrix in specific mapping rules. Meanwhile, a certain number of elite bases are preserved and updated iteratively according to the correlation coefficients with respect to the target model. The regression model is then spanned by the elite bases. A comparative study between EBR and a recent proposed machine learning method for symbolic regression, Fast Function eXtraction (FFX), are conducted. Numerical results indicate that EBR can solve symbolic regression problems more effectively. © 2017 IEEE.
KeywordData mining Fuzzy systems Genetic algorithms Genetic programming Iterative methods Learning systems Comparative studies Correlation coefficient Function extraction Large scale problem Machine learning methods Real time algorithms Symbolic regression Symbolic regression problems
Indexed ByEI
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Document Type会议论文
Affiliation1.State Key Laboratory of High Temperature Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, Beijing; 100190, China;
2.School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing; 100049, China
Recommended Citation
GB/T 7714
Chen C,Luo ZT,Jiang ZL. Elite bases regression: A real-time algorithm for symbolic regression[C]ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery,2017:529-535.
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