A Weighted Voting Classifier Based on Differential Evolution
Joint Authors
Cai, Jing
Zhang, Hongrui
Yang, Binbin
Zhang, Yong
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-22
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Ensemble learning is to employ multiple individual classifiers and combine their predictions, which could achieve better performance than a single classifier.
Considering that different base classifier gives different contribution to the final classification result, this paper assigns greater weights to the classifiers with better performance and proposes a weighted voting approach based on differential evolution.
After optimizing the weights of the base classifiers by differential evolution, the proposed method combines the results of each classifier according to the weighted voting combination rule.
Experimental results show that the proposed method not only improves the classification accuracy, but also has a strong generalization ability and universality.
American Psychological Association (APA)
Zhang, Yong& Zhang, Hongrui& Cai, Jing& Yang, Binbin. 2014. A Weighted Voting Classifier Based on Differential Evolution. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-1033720
Modern Language Association (MLA)
Zhang, Yong…[et al.]. A Weighted Voting Classifier Based on Differential Evolution. Abstract and Applied Analysis No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-1033720
American Medical Association (AMA)
Zhang, Yong& Zhang, Hongrui& Cai, Jing& Yang, Binbin. A Weighted Voting Classifier Based on Differential Evolution. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-1033720
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033720