Some remarks on allocatory and separatory linear discrimination

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

A random vector originates from one of r known normal populations having a common covariance matrix. We wish to reduce the dimension of the vector by means of a linear map from the original space down to a space of lower dimension while keeping the populations as separate as possible. The commonly used linear maps which are optimal for a class of measures of separation may be very poor in terms of a different criterion: the probability of correct classification calculated with no prior information about the population of origin.

Original languageEnglish (US)
Pages (from-to)323-330
Number of pages8
JournalJournal of Statistical Planning and Inference
Volume14
Issue number2-3
DOIs
StatePublished - 1986
Externally publishedYes

Keywords

  • Allocation
  • Linear discrimination
  • Probability of correct classification
  • Separation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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