The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Moderating the outputs of support vector machine classifiers
Abstract
In this paper, we extend the use of moderated outputs to the support vector machine (SVM) by making use of a relationship between SVM and the evidence framework. The moderated output is more in line with the Bayesian idea that the posterior weight distribution should be taken into account upon prediction, and it also alleviates the usual tendency of assigning overly high confidence to the estimated class memberships of the test patterns. Moreover, the moderated output derived here can be taken as an approximation to the posterior class probability. Hence, meaningful rejection thresholds can be assigned and outputs from several networks can be directly compared. Experimental results on both artificial and real-world data are also discussed.
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Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
A practical Bayesian framework for backpropagation networks
MacKay, D. J. C. (1992) · Neural Computation · doi:10.1162/neco.1992.4.3.448 · Cited by 2,917
Bernardo, J. M., & Smith, A. F. M. (1994) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316870 · Cited by 2,178
Mackay, D. J. C. (1995) · Network Computation in Neural Systems · doi:10.1088/0954-898x/6/3/011 · Cited by 915
Cited by
He, H., & Garcia, E. A. (2009) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2008.239 · Cited by 10,359
Bayesian Methods for Neural Networks and Related Models
Titterington, D. M. (2004) · Statistical Science · doi:10.1214/088342304000000099 · Cited by 162
Machine learning with a reject option: A survey
Hendrickx, K., Perini, L., Van der Plas, D., Meert, W., & Davis, J. (2024) · Machine Learning · doi:10.1007/s10994-024-06534-x · Cited by 134
Metadata
- Authors
- Kwok, J. T.-Y.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1999
- Volume
- 10
- Issue
- 5
- Pages
- 1018-1031
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2147993235
- Cited by
- 159
- References
- 4
- FWCI
- 5.29
- Type
- journal article
- Language
- en
- Open access
- closed
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