A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification
The common issues of high-dimensional gene expression data are that many of the genes may not be relevant, and there exists a high correlation among genes. Gene selection has been proven to be an effective way to improve the results of many classification methods. Sparse logistic regression using le...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
Springer Verlag
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/96970/ http://dx.doi.org/10.1007/s11634-018-0334-1 |
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| Institution: | Universiti Teknologi Malaysia |
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