An efficient approach to compute the threshold for multi-dimensional linear classifiers

DOI10.1016/j.patcog.2003.07.013zbMath1067.68601OpenAlexW2034371392MaRDI QIDQ1886660

Luis G. Rueda

Publication date: 18 November 2004

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2003.07.013

zbMATH Keywords

Linear classifiersError evaluationFisher's classifierNormally distributed classesThreshold computation

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (2)

A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes ⋮ Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes

Cites Work

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• On optimal pairwise linear classifiers for normal distributions: The \(d\)-dimensional case
• A Note on the Generation of Random Normal Deviates
• A linear constrained distance-based discriminant analysis for hyperspectral classification

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