Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach
作者： Tao Xiong , Jieping Ye , V. Cherkassky
关键词:
摘要: Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in high dimensional feature space. Less attention has focused on properties of resulting vectors and reduced In this paper, we present a new formulation The includes, as special cases, uncorrelated analysis (KUDA) orthogonal (KODA). KUDA are uncorrelated, while KODA to each other We theoretical derivations algorithms. experimental results show that both very competitive comparison with terms classification accuracy.
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W. J. Krzanowski, P. Jonathan, W. V. McCarthy, M. R. Thomas, Discriminant Analysis with Singular Covariance Matrices: Methods and Applications to Spectroscopic Data Applied statistics. ,vol. 44, pp. 101- 115 ,(1995) , 10.2307/2986198
Cheong Hee Park, Haesun Park, Nonlinear Discriminant Analysis Using Kernel Functions and the Generalized Singular Value Decomposition SIAM Journal on Matrix Analysis and Applications. ,vol. 27, pp. 87- 102 ,(2005) , 10.1137/S0895479804442334
J. Duchene, S. Leclercq, An optimal transformation for discriminant and principal component analysis IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 10, pp. 978- 983 ,(1988) , 10.1109/34.9121
Sarunas Raudys, Robert P.W. Duin, Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix Pattern Recognition Letters. ,vol. 19, pp. 385- 392 ,(1998) , 10.1016/S0167-8655(98)00016-6
Zhong Jin, Jing-Yu Yang, Zhong-Shan Hu, Zhen Lou, Face recognition based on the uncorrelated discriminant transformation Pattern Recognition. ,vol. 34, pp. 1405- 1416 ,(2001) , 10.1016/S0031-3203(00)00084-4
Jerome H. Friedman, Regularized Discriminant Analysis Journal of the American Statistical Association. ,vol. 84, pp. 165- 175 ,(1989) , 10.1080/01621459.1989.10478752
Zhizheng Liang, Pengfei Shi, Uncorrelated discriminant vectors using a kernel method Pattern Recognition. ,vol. 38, pp. 307- 310 ,(2005) , 10.1016/J.PATCOG.2004.06.006
F.S. Samaria, A.C. Harter, Parameterisation of a stochastic model for human face identification workshop on applications of computer vision. pp. 138- 142 ,(1994) , 10.1109/ACV.1994.341300
W. Zheng, L. Zhao, C. Zou, Foley-Sammon optimal discriminant vectors using kernel approach IEEE Transactions on Neural Networks. ,vol. 16, pp. 1- 9 ,(2005) , 10.1109/TNN.2004.836239
P.N. Belhumeur, J.P. Hespanha, D.J. Kriegman, Eigenfaces vs. Fisherfaces: recognition using class specific linear projection IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 19, pp. 711- 720 ,(1997) , 10.1109/34.598228