Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification
Joint Authors
Lu, Huijuan
Liu, Yanqiu
Yan, Ke
Xia, Haixia
An, Chunlin
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-23
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Embedding cost-sensitive factors into the classifiers increases the classification stability and reduces the classification costs for classifying high-scale, redundant, and imbalanced datasets, such as the gene expression data.
In this study, we extend our previous work, that is, Dissimilar ELM (D-ELM), by introducing misclassification costs into the classifier.
We name the proposed algorithm as the cost-sensitive D-ELM (CS-D-ELM).
Furthermore, we embed rejection cost into the CS-D-ELM to increase the classification stability of the proposed algorithm.
Experimental results show that the rejection cost embedded CS-D-ELM algorithm effectively reduces the average and overall cost of the classification process, while the classification accuracy still remains competitive.
The proposed method can be extended to classification problems of other redundant and imbalanced data.
American Psychological Association (APA)
Liu, Yanqiu& Lu, Huijuan& Yan, Ke& Xia, Haixia& An, Chunlin. 2016. Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099766
Modern Language Association (MLA)
Liu, Yanqiu…[et al.]. Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1099766
American Medical Association (AMA)
Liu, Yanqiu& Lu, Huijuan& Yan, Ke& Xia, Haixia& An, Chunlin. Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1099766
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099766