Enhancement of ELM by Clustering Discrimination Manifold Regularization and Multiobjective FOA for Semisupervised Classification
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
A novel semisupervised extreme learning machine (ELM) with clustering discrimination manifold regularization (CDMR) framework named CDMR-ELM is proposed for semisupervised classification.
By using unsupervised fuzzy clustering method, CDMR framework integrates clustering discrimination of both labeled and unlabeled data with twinning constraints regularization.
Aiming at further improving the classification accuracy and efficiency, a new multiobjective fruit fly optimization algorithm (MOFOA) is developed to optimize crucial parameters of CDME-ELM.
The proposed MOFOA is implemented with two objectives: simultaneously minimizing the number of hidden nodes and mean square error (MSE).
The results of experiments on actual datasets show that the proposed semisupervised classifier can obtain better accuracy and efficiency with relatively few hidden nodes compared with other state-of-the-art classifiers.
American Psychological Association (APA)
Ye, Qing& Pan, Hao& Liu, Changhua. 2015. Enhancement of ELM by Clustering Discrimination Manifold Regularization and Multiobjective FOA for Semisupervised Classification. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057745
Modern Language Association (MLA)
Ye, Qing…[et al.]. Enhancement of ELM by Clustering Discrimination Manifold Regularization and Multiobjective FOA for Semisupervised Classification. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1057745
American Medical Association (AMA)
Ye, Qing& Pan, Hao& Liu, Changhua. Enhancement of ELM by Clustering Discrimination Manifold Regularization and Multiobjective FOA for Semisupervised Classification. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057745
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057745