WIT Press


Hierachical Clustering For Data Mining By RBF Network

Price

Free (open access)

Paper DOI

10.2495/DATA000461

Volume

25

Pages

10

Published

2000

Size

869 kb

Author(s)

O. Ciftcioglu & S. Sariyildiz

Abstract

Hierarchical clustering for data mining by rbf network 6. Ciftcioglu & S. Sariyildiz Delft University of Technology Faculty of Architecture, Department of Informatics Delft, The Netherlands Abstract Clustering is one of the dominant techniques of exploratory data analysis. In the context of data mining, one of the powerful clustering methods is the method of orthogonal least squares (OLS) applied to radial basis functions (RBF) network. However, for data mining case, conventional utilization of OLS learning is not desirable even though the learning process feasible for an amount of data at hand. This is due to the fact that some dominant associations in the data can easily obscure many interrelations of interest among the data at hand and also because of this, the rest of the associations for identification can heavily be limited. Therefore, as novel RBF clustering for data mining, the data set is separated into several subsets so that each subset is subjected to clustering separate

Keywords