Abstract
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.
| Original language | English |
|---|---|
| Article number | 012039 |
| Journal | Journal of Physics: Conference Series |
| Volume | 1344 |
| Issue number | 1 |
| DOIs | |
| State | Published - 31 Oct 2019 |
| Event | International Conference on Recent Inventions and Innovations in Mathematical Sciences, ICRIIMS 2019 - Visakhapatnam, Andhra Pradesh, India Duration: 28 Feb 2019 → 1 Mar 2019 |
Keywords
- Clustering
- Fuzzy C-Means
- Kernel Distance
- heterogeneous databases
ASJC Scopus subject areas
- General Physics and Astronomy
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