
doi: 10.1007/bf02291704
This paper attempts to review and expand upon the relationship between graph theory and the clustering of a set of objects. Several graphtheoretic criteria are proposed for use within a general clustering paradigm as a means of developing procedures “in between” the extremes of complete-link and single-link hierarchical partitioning; these same ideas are then extended to include the more general problem of constructing subsets of objects with overlap. Finally, a number of related topics are surveyed within the general context of reinterpreting and justifying methods of clustering either through standard concepts in graph theory or their simple extensions.
Graph theory, Classification and discrimination; cluster analysis (statistical aspects), Applications of statistics to psychology
Graph theory, Classification and discrimination; cluster analysis (statistical aspects), Applications of statistics to psychology
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