Please use this identifier to cite or link to this item:
|Title:||An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels|
|Keywords:||Leave-one-out (LOO) error|
Support vector machines (SVMs)
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 22, 2018
WEB OF SCIENCETM
checked on Jun 19, 2018
checked on May 25, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.