Title :
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
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;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371198
