The Euclidean distance classifier: an alternative to the linear discriminant function

DOI10.1080/03610918708812601zbMath0622.62066OpenAlexW2054487136MaRDI QIDQ3759736

Virgil R. Marco, Dean M. Young, Danny W. Turner

Publication date: 1987

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918708812601

zbMATH Keywords

Mahalanobis distancesample linear discriminant functionprobability of correct classificationcomparison of classifiersnonspherical normal distributionsample Euclidean distance classifier

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

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Cites Work

• Unnamed Item
• Some asymptotic results on the effect of autocorrelation on the error rates of the sample linear discriminant function
• Effect of autocorrelated training samples on Bayes' probabilities of misclassification
• Further results on the effect of intraclass correlation among training samples in discriminant analysis
• On the Effects of Dimension in Discriminant Analysis for Unequal Covariance Populations
• On Dimensionality, Sample Size, Classification Error, and Complexity of Classification Algorithm in Pattern Recognition
• On the Effects of Dimension in Discriminant Analysis
• On the Classification of Observation Data into Distinct Groups