Accession Number:

AD0628709

Title:

TWO CLASSES OF NON-PARAMETRIC TECHNIQUES FOR PATTERN RECOGNITION AND THEIR ERROR ANALYSIS.

Descriptive Note:

Technical note,

Corporate Author:

INFORMATION RESEARCH ASSOCIATES INC CAMBRIDGE MASS

Personal Author(s):

Report Date:

1965-09-01

Pagination or Media Count:

23.0

Abstract:

Another criterion is added to handle the case when distributional information is lacking. This criterion is to approximate the Bayes Solution based only on the statistics acquired during the learning phase. This criterion approaches the optimum risk decision as the learning phase is increased. Two classes of nonparametric techniques are proposed. Corresponding error analyses for these two techniques are made in order to determine how much is lost by using sub-optimal i.e., a finite learning phase decisions. Author

Subject Categories:

  • Statistics and Probability
  • Bionics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE