A new fusion algorithm for fuzzy clustering

• Main Authors: Ivan Vidović, Dražen Bajer, Rudolf Scitovski
• Format: Article
• Language: English
• Published: Croatian Operational Research Society 2014-12-01
• Series: Croatian Operational Research Review
• Subjects: fusion algorithm; fuzzy clustering; Mahalanobis clustering; cluster merging; Davies-Bouldin index
• Online Access: http://hrcak.srce.hr/index.php?show=clanak&id_clanak_jezik=197354

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.