An Efficient Method for Computing Leave-One-Out Error in Support Vector Machines With Gaussian Kernels  

Oleh:

Keerthi, S. S. ; Lee, M. M. S. ; Chong, Jin Ong ; DeCoste, D.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 3 (May 2004), page 750-757.
Topik: gaussian; computing leave - one - out; error; support vector; machines; gaussian kernels

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper, we give an efficient method for computing the leave - one - out (LOO) error for support vector machines (SVM s) with Gaussian kernels quite accurately. It is particularly suitable for iterative decomposition methods of solving SVM s. 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.

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