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Feature Selection in Decision Systems: A Mean-Variance Approach
Joint Authors
Yang, Chengdong
Zhang, Wenyin
Zou, Jilin
Hu, Shunbo
Qiu, Jianlong
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-26
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Uncertainty measure is an important implement for characterizing the degree of uncertainty.
It has been extensively applied in pattern recognition and data clustering.
Because of instability of traditional uncertainty measures, mean-variance measure (MVM) is utilized to perform feature selection, which could depress disturbances and noises effectively.
Thereby, a novel evaluation function based on MVM is designed.
The forward greedy search algorithm (FGSA) with the proposed evaluation function is exploited to perform feature selection.
Experiment analysis shows the validity and effectiveness of MVM.
American Psychological Association (APA)
Yang, Chengdong& Zhang, Wenyin& Zou, Jilin& Hu, Shunbo& Qiu, Jianlong. 2013. Feature Selection in Decision Systems: A Mean-Variance Approach. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1008866
Modern Language Association (MLA)
Yang, Chengdong…[et al.]. Feature Selection in Decision Systems: A Mean-Variance Approach. Mathematical Problems in Engineering No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-1008866
American Medical Association (AMA)
Yang, Chengdong& Zhang, Wenyin& Zou, Jilin& Hu, Shunbo& Qiu, Jianlong. Feature Selection in Decision Systems: A Mean-Variance Approach. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1008866
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1008866