Experiments with some cluster analysis algorithms

Abstract In this paper, we shall show the following experimental results: (1) the one-dimensional clustering algorithm advocated by Slagle and Lee (1) can be generalized to the n -dimensional case, n > 1: (2) if a set of points in some n -space ( n > 1) are linearly ordered through the short spanning path algorithm, then this set of points can be considered as occupying a one-dimensional space and the original n -dimensional clustering problem can now be viewed as a one-dimensional clustering problem; (3) a short spanning path usually contains as much information as a minimal spanning tree; (4) the one-dimensional clustering algorithm can be used to find the long links in a short spanning path or a minimal spanning tree. These long links have to be broken to obtain clusters.