Data clustering analysis in a multidimensional space

Cluster analysis techniques are used to classify objects into groups based on their similarities. There is a wide choice of methods with different requirements in computer resources. We present the result of a fairly exhaustive study to evaluate three commonly used clustering algorithms, namely, single linkage, complete linkage, and centroid. The cluster analysis study is conducted in the two dimensional (2-D) space. Three types of statistical distribution are used. Two different types of distances to compare lists of objects are also used. The results point to some startling, similarities in the behavior and stability of all clustering methods. (C) 1998 Elsevier Science Inc. All rights reserved.