Mathematical Tools of Cluster Analysis

Peter Trebuňa; Jana Halčinová

doi:10.4236/am.2013.45111

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Applied Mathematics > Vol.4 No.5, May 2013

Mathematical Tools of Cluster Analysis ()

Peter Trebuňa, Jana Halčinová

Department of Industrial Engineering and Management, Technical University of Ko?ice, Ko?ice, Slovakia.

DOI: 10.4236/am.2013.45111 PDF HTML XML 4,083 Downloads 6,485 Views Citations

Abstract

The paper deals with cluster analysis and comparison of clustering methods. Cluster analysis belongs to multivariate statistical methods. Cluster analysis is defined as general logical technique, procedure, which allows clustering variable objects into groups-clusters on the basis of similarity or dissimilarity. Cluster analysis involves computational procedures, of which purpose is to reduce a set of data on several relatively homogenous groups-clusters, while the condition of reduction is maximal and simultaneously minimal similarity of clusters. Similarity of objects is studied by the degree of similarity (correlation coefficient and association coefficient) or the degree of dissimilarity-degree of distance (distance coefficient). Methods of cluster analysis are on the basis of clustering classified as hierarchical or non-hierarchical methods.

Keywords

Cluster Analysis; Hierarchical Cluster Analysis Methods; Non-Hierarchical Cluster Analysis Methods

Share and Cite:

P. Trebuňa and J. Halčinová, "Mathematical Tools of Cluster Analysis," Applied Mathematics, Vol. 4 No. 5, 2013, pp. 814-816. doi: 10.4236/am.2013.45111.

Conflicts of Interest

The authors declare no conflicts of interest.

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