Title
Improving clustering technique for functional approximation problem using fuzzy logic: ICFA algorithm
Abstract
Clustering algorithms have been applied in several disciplines successfully. One of those applications is the initialization of Radial Basis Functions (RBF) centers composing a Neural Network, designed to solve functional approximation problems. The Clustering for Function Approximation (CFA) algorithm was presented as a new clustering technique that provides better results than other clustering algorithms that were traditionally used to initialize RBF centers. Even though CFA improves performance against other clustering algorithms, it has some flaws that can be improved. Within those flaws, it can be mentioned the way the partition of the input data is done, the complex migration process, the algorithm's speed, the existence of some parameters that have to be set in order to obtain good solutions, and the convergence is not guaranteed. In this paper, it is proposed an improved version of this algorithm that solves the problems that its predecessor has using fuzzy logic successfully. In the experiments section, it will be shown how the new algorithm performs better than its predecessor and how important is to make a correct initialization of the RBF centers to obtain small approximation errors.
Year
DOI
Venue
2005
10.1007/11494669_34
IWANN
Keywords
Field
DocType
fuzzy logic,icfa algorithm,clustering algorithm,function approximation,better result,small approximation error,functional approximation problem,new clustering technique,new algorithm,improved version,correct initialization,rbf center,neural network,approximation error
Canopy clustering algorithm,Approximation algorithm,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Computer science,Algorithm,Constrained clustering,Cluster analysis,Approximation error
Conference
Volume
ISSN
ISBN
3512
0302-9743
3-540-26208-3
Citations 
PageRank 
References 
16
0.82
6
Authors
7
Name
Order
Citations
PageRank
A. Guillén118220.83
I. Rojas21750143.09
Jesús González360444.40
H. Pomares472244.28
L. J. Herrera533024.45
O. Valenzuela619611.42
A. Prieto718712.72