Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space
type: Item
instance of: scholarly article
title: Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space
zbMATH Open document ID: 1162.68639
author: Kuo-Ping Wu
author: Sheng-D. Wang
published in: Pattern Recognition
publication date: 2009-04-03T00:00:00Z
full work available at URL: http://ntur.lib.ntu.edu.tw//handle/246246/142303
Mathematics Subject Classification ID: 68T10
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5539753
zbMATH Keywords: SVM
zbMATH Keywords: support vector machines
zbMATH Keywords: kernel parameters
zbMATH Keywords: inter-cluster distances
describes a project that uses: Torch
describes a project that uses: LIBSVM
MaRDI profile type: Publication
OpenAlex ID: W2153272791
cites work: Q4261789
cites work: A method to make multiple hypotheses with high cumulative recognition rate using SVMs.
cites work: Polynomial-time decomposition algorithms for support vector machines
cites work: Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
cites work: Q4843404
DOI: 10.1016/J.PATCOG.2008.08.030
description: scientific article; zbMATH DE number 5539753