On Discrete Variables in Pattern Recognition.

Abstract

DISCRIMINATE ANALYSIS, DISCRIMINANT FUNCTIONSThe central problem dealt with in the report concerns pattern recognition tasks which involve discrete measurement variables. In the first chapter, the particular difficulties associated with discrete variables in the pattern recognition discipline are illuminated. The next chapter presents historical evidence of the variety of techniques applied to the task of dealing with discrete variables in the context of a classification problem. The third chapter provides a derivation of the aposteriori probability distribution for the error rate in a discrete variable classification problem. In Chapter 4, the theoretical foundation for the proposed procedure of dealing with discrete variable classifier design tasks is presented. Chapter 5 contains an analysis of the proposed method of applying the theory of prime events and an example application of the method to a discrete variable design task. (Author Modified Abstract)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1973
Accession Number
AD0756495

Entities

People

  • James Stoffel

Organizations

  • Syracuse University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Classification
  • Discriminate Analysis
  • Machine Learning
  • Mathematics
  • Measurement
  • Pattern Recognition
  • Probability
  • Probability Distributions
  • Recognition

Readers

  • Business Analytics
  • Neural Network Machine Learning.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference