Group-size dependence: a rationale for choice between numerical classifications

Abstract

The problem of erecting criteria for choice between numerical classificationsis briefly surveyed: it is concluded that the most difficult casearises in the synoptic classification of highly heterogeneous data,for which a powerful clustering system is essential, and for whichseveral alternative strategies are in common use. In all such strategiesan inter-group or individual-group measure is dependent on the sizeof the group, but the nature of this dependence has not previouslybeen investigated. It is here investigated for four widely-used strategies,and appropriate conclusions drawn as to their differing applicabilityto particular types of problem.