Linear dimensionality reduction using relevance weighted LDA

DOI10.1016/j.patcog.2004.09.005zbMath1079.68613OpenAlexW1999250675WikidataQ56594398 ScholiaQ56594398MaRDI QIDQ2485060

Yanyan Li

Publication date: 3 August 2005

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2004.09.005

zbMATH Keywords

Linear discriminant analysisMahalanobis distanceFeature extractionEvolution strategiesApproximate pairwise accuracy criterionChernoff criterionWeighted LDA

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (8)

A study on three linear discriminant analysis based methods in small sample size problem ⋮ Pareto models for discriminative multiclass linear dimensionality reduction ⋮ Modified hybrid discriminant analysis methods and their applications in machine learning ⋮ Maxi-Min discriminant analysis via online learning ⋮ Misclassification analysis of discriminant model ⋮ A study of regularized Gaussian classifier in high-dimension small sample set case based on MDL principle with application to spectrum recognition ⋮ Recent advances in evolutionary computation ⋮ Generalizing relevance weighted LDA

Uses Software

• UCI-ml

Cites Work

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• On the relation between discriminant analysis and mutual information for supervised linear feature extraction
• THE STATISTICAL UTILIZATION OF MULTIPLE MEASUREMENTS
• Face recognition based on the uncorrelated discriminant transformation
• A direct LDA algorithm for high-dimensional data -- with application to face recognition

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