Original scientific paper
https://doi.org/10.17535/crorr.2014.0004
A new fusion algorithm for fuzzy clustering
Ivan Vidović
; Faculty of Electrical Engineering Osijek, Josip Juraj Strossmayer University of Osijek
Dražen Bajer
; Faculty of Electrical Engineering Osijek, Josip Juraj Strossmayer University of Osijek
Rudolf Scitovski
; Department of Mathematics, Josip Juraj Strossmayer University of Osijek
Abstract
In this paper, we have considered the merging problem of two ellipsoidal clusters in order to construct a new fusion algorithm for fuzzy clustering. We have proposed a criterion for merging two ellipsoidal clusters ∏1, ∏2 with associated main Mahalanobis circles Ej(cj,σj), where cj is the centroid and σ^2j is the Mahalanobis variance of cluster ∏j . Based on the well-known Davies-Bouldin index, we have constructed a new fusion algorithm. The criterion has been tested on several data sets, and the performance of the fusion algorithm has been demonstrated on an illustrative example.
Keywords
fusion algorithm; fuzzy clustering; Mahalanobis clustering; cluster merging; Davies-Bouldin index
Hrčak ID:
133693
URI
Publication date:
30.12.2014.
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