A Model for Ordinal Nonhierarchical Cluster Methods.

Abstract

Hierarchical clustering involves the creation of a nested sequence of partitions of a set, whereas nonhierarchical clustering deals with a single partition. Nonhierarchical cluster techniques come up in a variety of situations involving such items as: (i) the assignment of stars to galaxies, (ii) the assignment of grades to students by an instructor; (iii) the classification of psychiatric patients by diagnostic type; (iv) the classification of rock formations: (v) the interpretation of LANDSAT images; (vi) automatic target detection; (vii) the grouping of companies according to properties that their stock might have in the stock market. It is not our purpose here to survey the literature in this area - rather, the reader is referred to standard references. As in our earlier model for hierarchical clustering, the viewpoint here will be that the input data has only ordinal significance. The order theoretic properties of the resulting model are offered in Section 2 and it will be related to some earlier theoretical work in Section 3. Finally, Section 4 presents an abstract characterization of the model in terms of semiBoolean algebras.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1981
Accession Number
ADA107111

Entities

People

  • M. F. Janowitz

Organizations

  • University of Massachusetts Amherst

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Boolean Algebra
  • Classification
  • Clustering
  • Computations
  • Construction
  • Detection
  • Inequalities
  • Instructors
  • Intervals
  • Massachusetts
  • Materials
  • Mathematics
  • Numbers
  • Permutations
  • Real Numbers
  • Target Detection

Readers

  • Business Analytics
  • Regression Analysis.
  • Theoretical Analysis.