STATISTICAL TECHNIQUE IN CLUSTERING AND PATTERN RECOGNITION.

Abstract

Several techniques in clustering and pattern recognition are examined and evaluated. In each the objective is to partition the elements of a specified population into subsets so that the partition meets conditions imposed by the problems. The basic metric employed is the distance between elements. The question of sampling techniques in clustering is investigated because total enumeration of partitions very quickly becomes inordinately high. Several specific examples are worked out. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 18, 1968
Accession Number
AD0681029

Entities

People

  • Paul Switzer

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Clustering
  • Pattern Recognition
  • Recognition
  • Sampling

Readers

  • Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • AI & ML