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|Title:||An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels||Authors:||Lee, M.M.S.
|Keywords:||Leave-one-out (LOO) error
Support vector machines (SVMs)
|Issue Date:||May-2004||Citation:||Lee, M.M.S., Keerthi, S.S., Ong, C.J., DeCoste, D. (2004-05). An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels. IEEE Transactions on Neural Networks 15 (3) : 750-757. ScholarBank@NUS Repository. https://doi.org/10.1109/TNN.2004.824266||Abstract:||In this paper, we give an efficient method for computing the leave-one-out (LOO) error for support vector machines (SVMs) with Gaussian kernels quite accurately. It is particularly suitable for iterative decomposition methods of solving SVMs. The importance of various steps of the method is illustrated in detail by showing the performance on six benchmark datasets. The new method often leads to speedups of 10-50 times compared to standard LOO error computation. It has good promise for use in hyperparameter tuning and model comparison.||Source Title:||IEEE Transactions on Neural Networks||URI:||http://scholarbank.nus.edu.sg/handle/10635/59442||ISSN:||10459227||DOI:||10.1109/TNN.2004.824266|
|Appears in Collections:||Staff Publications|
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