A Novel Local Classification Method using Growing Neural Gas and Proximal Support Vector Machines

Author

Rodríguez-Pena, Rubén M. ; Pérez-Sánchez, Beatriz ; Fontenla-Romero, Oscar

Author_Institution

Univ. of A Corua, A Corua

fYear

2007

fDate

12-17 Aug. 2007

Firstpage

1607

Lastpage

1612

Abstract

In this paper, a new pattern recognition method is presented. It is based on the combination of two techniques. The first is a modified version of growing neural gas, and the second is a set of proximal support vector machines. The aim of the former is to obtain a topology in the network that defines different local regions into the input space; and the goal of the latter is to fit a set of local classifiers for each one of the regions. The efficiency of the algorithm is validated on two data sets and is compared to another standard algorithm. The results obtained by the method presented exhibit a good performance in all cases.

Keywords

neural nets; pattern classification; support vector machines; local classification method; network topology; neural gas; pattern recognition method; support vector machine; Approximation algorithms; Classification algorithms; Clustering algorithms; Jacobian matrices; Network topology; Neural networks; Pattern recognition; Regression tree analysis; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2007. IJCNN 2007. International Joint Conference on

Conference_Location

Orlando, FL

ISSN

1098-7576

Print_ISBN

978-1-4244-1379-9

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2007.4371198

Filename

4371198