INCOMPLETE PRIOR INFORMATION IN A CLASSIFICATION PROCEDURE.

Abstract

The classification of specimens into one of N populations is considered when the observation on each specimen is a multivariate discrete random variable and when incomplete prior information is available concerning the occurrence of specimens from the various populations. The T-minimax decision criterion is applied and it is shown that an optimal classification procedure is the solution of a finite matrix game. The consistency of the T-minimax procedure is demonstrated when certain population probabilities are estmated by sample proportions. A medical example is considered. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1970
Accession Number
AD0712031

Entities

People

  • Myles Hollander
  • Ronald H. Randles

Organizations

  • Florida State University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Classification
  • Consistency
  • Mathematics
  • Matrix Games
  • Observation
  • Probability
  • Probability Distributions
  • Random Variables

Fields of Study

  • Mathematics

Readers

  • Clinical Trial Research.
  • Mathematical Modeling and Probability Theory.
  • Neural Network Machine Learning.