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Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection
Joint Authors
Li, Jun-Tao
Chen, Liuyuan
Yang, Jie
Wang, Xiaoyu
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-31
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
For the multiclass classification problem of microarray data, a new optimization model named multinomial regression with the elastic net penalty was proposed in this paper.
By combining the multinomial likeliyhood loss and the multiclass elastic net penalty, the optimization model was constructed, which was proved to encourage a grouping effect in gene selection for multiclass classification.
American Psychological Association (APA)
Chen, Liuyuan& Yang, Jie& Li, Jun-Tao& Wang, Xiaoyu. 2014. Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1033839
Modern Language Association (MLA)
Chen, Liuyuan…[et al.]. Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection. Abstract and Applied Analysis No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1033839
American Medical Association (AMA)
Chen, Liuyuan& Yang, Jie& Li, Jun-Tao& Wang, Xiaoyu. Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1033839
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033839