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Clustering Algorithms
Clustering algorithms
Introduction

Clustering analysis is a multivariate analysis technique that seeks to organize objects described by a number of attributes or variables into relatively homogeneous groups, or ‘clusters’. An optimal solution of clustering problems can be obtained by comparing the performance criterion of all combinations of objects. For this reason, problems with small numbers of objects can be solved exactly. For the large problem, however, such exhaustive enumeration approaches would be impractical since the number of combinations grows exponentially with the number of objects. Because of the ill-defined nature of cluster analysis problems, many different types of cluster analysis algorithms have been proposed. Anderberg (1973) separated clustering methods into two types: hierarchical and non-hierarchical clustering methods. We will review these two types of methods in ...

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