TY - GEN
T1 - An experimental study
T2 - 2002 International Conference on Machine Learning and Cybernetics
AU - Huang, Rong Bo
AU - Law, Lap Tak
AU - CHEUNG, Yiu Ming
N1 - Copyright:
Copyright 2004 Elsevier Science B.V., Amsterdam. All rights reserved.
PY - 2002
Y1 - 2002
N2 - This paper experimentally investigates Indep- endent Component Analysis (ICA) and Principle Component Analysis (PCA) on reducing the input dimension of a Radial Basis Function (RBF) network such that the net's complexity is reduced. The results have shown that a RBF network with ICA as an input pre-process has the similar generalization ability to the one without pre-processing, but the former's performance converges much faster. In contrast, a PCA based RBF however leads to a deteriorated result in both convergent speed and the generalization ability.
AB - This paper experimentally investigates Indep- endent Component Analysis (ICA) and Principle Component Analysis (PCA) on reducing the input dimension of a Radial Basis Function (RBF) network such that the net's complexity is reduced. The results have shown that a RBF network with ICA as an input pre-process has the similar generalization ability to the one without pre-processing, but the former's performance converges much faster. In contrast, a PCA based RBF however leads to a deteriorated result in both convergent speed and the generalization ability.
UR - http://www.scopus.com/inward/record.url?scp=0036926754&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0036926754
SN - 0780375084
T3 - Proceedings of 2002 International Conference on Machine Learning and Cybernetics
SP - 1941
EP - 1945
BT - Proceedings of 2002 International Conference on Machine Learning and Cybernetics
Y2 - 4 November 2002 through 5 November 2002
ER -