17th International Conference on Pattern Recognition (ICPR'04) - Volume 3 Fast Leave-One-Out Evaluation and Improvement on Inference for LS-SVMs Cambridge UK August 23-August 26 ISBN: 0-7695-2128-2
In this paper, a fast leave-one-out (LOO) evaluation formula is introduced for least squares support vector machine (LS-SVM) classifiers. The computation cost can be reduced to approximately 1/N when compared to normal LOO procedure (is the number of training samples). Inspired by its fast speed, we are able to use it to replace the original Level 3 posterior probability approximation formula of the Bayesian framework [Bayesian framework for least squares support vector machine classifiers, gaussian processes and kernel fisher discriminant analysis] for LS-SVM classifiers. The improved inference framework shows higher generalization performance and faster computation speed.
Citation:
Zhao Ying, Kwoh Chee Keong, "Fast Leave-One-Out Evaluation and Improvement on Inference for LS-SVMs," icpr, vol. 3, pp.494-497, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 3, 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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