TITLE:
Mathematical Tools of Cluster Analysis
AUTHORS:
Peter Trebuňa, Jana Halčinová
KEYWORDS:
Cluster Analysis; Hierarchical Cluster Analysis Methods; Non-Hierarchical Cluster Analysis Methods
JOURNAL NAME:
Applied Mathematics,
Vol.4 No.5,
May
20,
2013
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.