✦ LIBER ✦

Linear programming support vector machines

✍ Scribed by Weida Zhou; Li Zhang; Licheng Jiao

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 250 KB
Volume: 35
Category: Article
ISSN: 0031-3203
DOI: 10.1016/s0031-3203(01)00210-2

No coin nor oath required. For personal study only.

✦ Synopsis

Based on the analysis of the conclusions in the statistical learning theory, especially the VC dimension of linear functions, linear programming support vector machines (or SVMs) are presented including linear programming linear and nonlinear SVMs. In linear programming SVMs, in order to improve the speed of the training time, the bound of the VC dimension is loosened properly. Simulation results for both artiÿcial and real data show that the generalization performance of our method is a good approximation of SVMs and the computation complex is largely reduced by our method.

📜 SIMILAR VOLUMES

Support vector fuzzy regression machines

✍ Dug Hun Hong; Changha Hwang 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 289 KB

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems. In this paper, we introduce the use of SVM for multivariate fuzzy linear and nonlinear regression models. Using the basic idea underlying SVM for multivariate fuzzy regressions gives comput

Applicational aspects of support vector

Applicational aspects of support vector machines

✍ A. I. Belousov; S. A. Verzakov; J. von Frese 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 227 KB

Support Vector Machines are Universally

Support Vector Machines are Universally Consistent

✍ Ingo Steinwart 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 220 KB

We show that support vector machines of the 1-norm soft margin type are universally consistent provided that the regularization parameter is chosen in a distinct manner and the kernel belongs to a specific class}the so-called universal kernels}which has recently been considered by the author. In par

Density-induced margin support vector ma

Density-induced margin support vector machines

✍ Li Zhang; Wei-Da Zhou 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 503 KB

This paper proposes a new classifier called density-induced margin support vector machines (DMSVMs). DMSVMs belong to a family of SVM-like classifiers. Thus, DMSVMs inherit good properties from support vector machines (SVMs), e.g., unique and global solution, and sparse representation for the decisi

Maximal Discrepancy for Support Vector M

Maximal Discrepancy for Support Vector Machines

✍ Davide Anguita; Alessandro Ghio; Sandro Ridella 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 314 KB

Incident detection using support vector

Incident detection using support vector machines

✍ Fang Yuan; Ruey Long Cheu 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 256 KB

This paper presents the applications of a recently developed pattern classifier called support vector machine (SVM) in incident detection. Support vector machine is constructed from a unique learning algorithm that extracts training vectors that lie closest to the class boundary, and makes use of th