Hierachical Clustering For Data Mining By RBF Network
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
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