Mark Last

Senior Academic

Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

S. R. Kannan, M. Siva, R. Devi, S. Ramathilagam, Mark Last

The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted bias field information, kernel distance, possibilistic memberships and fuzzy memberships into memberships equation and prototype equation. The effectiveness and efficiency of the proposed clustering techniques have been shown through the experimental results on benchmark heterogeneous databases.

Publication language English
Journal Journal of Physics: Conference Series
Volume 1344
Issue number 1
Publication status Published - 31.10.2019
Article Number 012039

Keywords

Clustering
Fuzzy C-Means
Kernel Distance
heterogeneous databases

ASJC Scopus subject areas

General Physics and Astronomy