A new linear discriminant analysis algorithm based on L1-norm maximization and locality preserving projection

DOI10.1007/S10044-017-0594-YzbMath1425.68360OpenAlexW2587684481MaRDI QIDQ2337653

Minghui Du, Jiazhong He, Xue-Qiang Li, Dianzhou Zhang

Publication date: 20 November 2019

Published in: PAA. Pattern Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10044-017-0594-y

zbMATH Keywords

L1-normL2-normfeature extractionpattern classificationlinear discriminant analysislocal information

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Uses Software

• UCI-ml
• KPCA plus LDA
• ORL face

Cites Work

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• A novel supervised dimensionality reduction algorithm: graph-based Fisher analysis
• Efficient linear discriminant analysis with locality preserving for face recognition
• Global plus local: a complete framework for feature extraction and recognition
• Two-dimensional supervised local similarity and diversity projection
• Stable local dimensionality reduction approaches
• Linear Discriminant Analysis Based on L1-Norm Maximization
• A direct LDA algorithm for high-dimensional data -- with application to face recognition

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