Research on Least Squares Support Vector Machines Algorithm

DOI

10.2991/iiicec-15.2015.318How to use a DOI?

Keywords

classification algorithm; SVM; least square support vector machine; kernel function

Abstract

Support vector machine is a classification algorithm emerged in recent years and has been successfully applied to many areas, and least squares support vector machine is a technology developed from the traditional support vector machine and has important researching significance. Firstly, this paper introduces the basic idea of SVM and algorithms; secondly to study the basic principles of least squares support vector machine, concrete algorithm description, including the kernel function, etc; finally, this paper studied the application of the algorithm in the classification, the least squares support vector machine as a novel artificial intelligence technology is an extension of the standard support vector machine and has been more widely used in various disciplines, with global optimization, good marketing ability and other features, so this research has some theoretical significance.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ming Zhao
PY  - 2015/03
DA  - 2015/03
TI  - Research on Least Squares Support Vector Machines Algorithm
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 1432
EP  - 1435
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.318
DO  - 10.2991/iiicec-15.2015.318
ID  - Zhao2015/03
ER  -