About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
Pattern Recognition
Paper
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. © 1974.