Linear dimensionality reduction by maximizing the Chernoff distance in the transformed space

Pattern Recognition

Volumn 41, Issue 10, 2008, Pages 3138-3152

  Rueda, Luis ^a   Herrera, Myriam ^b  

^a UNIVERSITY OF CONCEPCIÓN   (Chile)

^b UNIVERSIDAD NACIONAL DE SAN JUAN   (Argentina)

Author keywords

Discriminant analysis; Linear dimensionality reduction; Pattern classification

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; CONVERGENCE OF NUMERICAL METHODS; FEATURE EXTRACTION; LEARNING SYSTEMS; PATTERN RECOGNITION; QUADRATIC PROGRAMMING; SET THEORY; STANDARDS;

(N-1) CRITERION; CHERNOFF DISTANCE; CLASS SEPARABILITY; COMPREHENSIVE PERFORMANCE ANALYSIS; CONVERGENCE (MATHEMATICS); ELSEVIER (CO); GRADIENT-BASED ALGORITHMS; LINEAR DIMENSIONALITY; LINEAR TIME COMPLEXITY; REAL-LIFE DATA; REAL-LIFE DATA SETS;

EIGENVALUES AND EIGENFUNCTIONS;

EID: 45849107211     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.01.016     Document Type: Article

References (22)

1. Duda R., Hart P., and Stork D. Pattern Classification. second ed. (2000), Wiley, New York, NY
2. Yu H., and Yang J. A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recognition 34 10 (2001) 2067-2070
3. Lu J., Plataniotis K., and Venetsanopoulos A. Face recognition using kernel direct discriminant analysis algorithms. IEEE Trans. Neural Networks 14 1 (2003) 117-126
4. Yang J., and Yang J.Y. Why can LDA be performed in PCA transformed space?. Pattern Recognition 36 2 (2003) 563-566
5. Yang J., Frangi A., Yang J.Y., Zhang D., and Zhong J. KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 27 2 (2005) 230-244
6. Yang J., Zhang D., Yong X., and Yang J.Y. Two-dimensional discriminant transform for face recognition. Pattern Recognition 38 7 (2005) 1125-1129
7. Martinez A., and Zhu M. Where are linear feature extraction methods applicable?. IEEE Trans. Pattern Anal. Mach. Intell. 27 12 (2005) 1934-1944
8. Rueda L., and Oommen B.J. On optimal pairwise linear classifiers for normal distributions: the two-dimensional case. IEEE Trans. Pattern Anal. Mach. Intell. 24 2 (2002) 274-280
9. Rueda L. Selecting the best hyperplane in the framework of optimal pairwise linear classifiers. Pattern Recognition Lett. 25 2 (2004) 49-62
10. M. Rohl, C. Weihs, Optimal vs. classical linear dimension reduction, In: Information Age, Studies in Classification, Data Analysis, and Knowledge Organization, Springer, Berlin, 1999, pp. 252-259.
11. Zhu M., and Martinez A. Subclass discriminant analysis. IEEE Trans. Pattern Anal. Mach. Intell. 28 8 (2006) 1262-1273
12. Loog M., and Duin P.W. Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion. IEEE Trans. Pattern Anal. Mach. Intell. 26 6 (2004) 732-739
13. Herrera M., and Leiva R. Generalización de la Distancia de Mahalanobis para el Análisis Discriminante Lineal en Poblaciones con Matrices de Covarianza Desiguales. Rev. Soc. Argent. Estadística 3 1-2 (1999) 64-86
14. Chong E., and Zak S. An Introduction to Optimization. second ed. (2001), Wiley, New York, NY
15. Abe S. Support Vector Machines for Pattern Classification (2005), Springer, Berlin
16. Newman D., Hettich S., Blake C., and Merz C. UCI Repository of Machine Learning Databases (1998), Department of Computer Science, University of California, Irvine
17. Rice J. Mathematical Statistics and Data Analysis. second ed. (1995), Duxbury Press, Belmont
18. Mintseris J., and Weng Z. Structure, function, and evolution of transient and obligate protein-protein interactions. Proc. Natl. Acad. Sci. USA 102 31 (2005) 10930-10935
19. Camacho C., and Zhang C. Fast contact: rapid estimate of contact and binding free energies. Bioinformatics 21 10 (2005) 2534-2536
20. Lu J., Plataniotis K., Venetsanopoulos A., and Li S. Ensemble-based discriminant learning with boosting for face recognition. IEEE Trans. Neural Networks 17 1 (2006) 166-178
21. Harville D. Matriz Algebra from a Statistician's Perspective (1997), Springer, New York
22. Stinson D. Cyptography: Theory and Practice. second ed. (2002), CRC Press, Boca Raton