Misclassification Rates of Likelihood and Predictive Discriminant Functions for Small Samples

Abstract

Likelihood and predictive discriminant function misclassification rates are compared when training sets are small (i.e., less than 20). The theoretical foundations for the linear, quadratic, and predictive discriminant functions are described. Simulations are used to compare the classification capability of each discriminant function while varying the variance of the underlying distributions. A multivariate case is also analyzed.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1992
Accession Number
ADA253640

Entities

People

  • Don Waagen

Organizations

  • Naval Command, Control and Ocean Surveillance Center

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Bayesian Networks
  • Computational Science
  • Data Science
  • Discriminant Analysis
  • Information Science
  • Knowledge Management
  • Monte Carlo Method
  • National Security
  • Pattern Recognition
  • Probability
  • Security
  • Simulations
  • Standards
  • Statistical Analysis
  • Statistics
  • Training

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.