The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Fast exact leave-one-out cross-validation of sparse least-squares support vector machines
Abstract
Leave-one-out cross-validation has been shown to give an almost unbiased estimator of the generalisation properties of statistical models, and therefore provides a sensible criterion for model selection and comparison. In this paper we show that exact leave-one-out cross-validation of sparse Least-Squares Support Vector Machines (LS-SVMs) can be implemented with a computational complexity of only O(ln2) floating point operations, rather than the O(l2n2) operations of a naïve implementation, where l is the number of training patterns and n is the number of basis vectors. As a result, leave-one-out cross-validation becomes a practical proposition for model selection in large scale applications. For clarity the exposition concentrates on sparse least-squares support vector machines in the context of non-linear regression, but is equally applicable in a pattern recognition setting.
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A tutorial on support vector machine-based methods for classification problems in chemometrics
Luts, J., Ojeda, F., Van de Plas, R., De Moor, B., Van Huffel, S., & Suykens, J. A. K. (2010) · Analytica Chimica Acta · doi:10.1016/j.aca.2010.03.030 · Cited by 326
An, S., Liu, W., & Venkatesh, S. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2006.12.015 · Cited by 301
Detection of early prognostic biomarkers for metastasis of Ewing's sarcoma in pediatric patients
Ezzeldin, S., Osama, A., Anwar, A. M., Mahgoub, S., Ahmed, E. A., Farid, N., Zamzam, M., El Ghoneimy, A., & Magdeldin, S. (2023) · Life Sciences · doi:10.1016/j.lfs.2023.122237 · Cited by 12
Metadata
- Authors
- Cawley, G. C., & Talbot, N. L. C.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2004-12
- Volume
- 17
- Issue
- 10
- Pages
- 1467-1475
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2069659771
- Cited by
- 332
- References
- 49
- FWCI
- 7.46
- Type
- journal article
- Language
- en
- Open access
- closed
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