An Optimization Algorithm for Cluster Analysis,

Abstract

Given a set of N points and distances between all points, the paper presents an algorithm for determining an optimal partition of the points into k mutually exclusive and exhaustive subsets or clusters according to an objective function defined on the set of all partitions. The value of the objective function for a given partition is defined as the maximum within-cluster distance in the partition. The algorithm determines an optimal partition by solving a sequence of set-covering problems. The set-covering problems have no more than N constraints and typically less than 1.5N variables. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1972
Accession Number
AD0751831

Entities

People

  • Chris Roach

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Coverings
  • Heuristic Methods
  • Mathematics
  • Optimization

Fields of Study

  • Computer science

Readers

  • Operations Research
  • Regression Analysis.