๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Text classification: A least square support vector machine approach

โœ Scribed by Vikramjit Mitra; Chia-Jiu Wang; Satarupa Banerjee


Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
280 KB
Volume
7
Category
Article
ISSN
1568-4946

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Robustified least squares support vector
โœ Michiel Debruyne; Sven Serneels; Tim Verdonck ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 274 KB

## Abstract Support vector machine (SVM) algorithms are a popular class of techniques to perform classification. However, outliers in the data can result in bad global misclassification percentages. In this paper, we propose a method to identify such outliers in the SVM framework. A specific robust

Chaos control using least-squares suppor
โœ Suykens, J. A. K.; Vandewalle, J. ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 118 KB

In this paper we apply a recently proposed technique of optimal control by support vector machines (SVMs) to chaos control. Vapnik's support vector method, which is based on the structural risk minimization principle and has been very successful in classi"cation and function estimation problems, is