The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
APPLICATIONS OF SUPPORT VECTOR MACHINES TO CANCER CLASSIFICATION WITH MICROARRAY DATA
Abstract
Microarray gene expression data usually have a large number of dimensions, e.g., over ten thousand genes, and a small number of samples, e.g., a few tens of patients. In this paper, we use the support vector machine (SVM) for cancer classification with microarray data. Dimensionality reduction methods, such as principal components analysis (PCA), class-separability measure, Fisher ratio, and t-test, are used for gene selection. A voting scheme is then employed to do multi-group classification by k(k - 1) binary SVMs. We are able to obtain the same classification accuracy but with much fewer features compared to other published results.
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Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Khan, J., Wei, J. S., Ringnér, M., Saal, L. H., Ladanyi, M., Westermann, F., Berthold, F., Schwab, M., Antonescu, C. R., Peterson, C., et al. (2001) · Nature Medicine · doi:10.1038/89044 · Cited by 2,644
Cover, T. M. (1965) · IEEE Transactions on Electronic Computers · doi:10.1109/pgec.1965.264137 · Cited by 2,044
Cited by
Feature selection methods for big data bioinformatics: A survey from the search perspective
Wang, L., Wang, Y., & Chang, Q. (2016) · Methods · doi:10.1016/j.ymeth.2016.08.014 · Cited by 331
Self-citation
Metadata
- Authors
- CHU, F., & WANG, L.
- Venue
- International Journal of Neural Systems
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 2005-12
- Volume
- 15
- Issue
- 06
- Pages
- 475-484
- ISSN
- 0129-0657 (ISSN-L)
- 1793-6462
- OpenAlex
- W2134837462
- Cited by
- 183
- References
- 3
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- CHU, F., & WANG, L. (2005). APPLICATIONS OF SUPPORT VECTOR MACHINES TO CANCER CLASSIFICATION WITH MICROARRAY DATA. International Journal of Neural Systems. https://doi.org/10.1142/s0129065705000396
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