|
|
|
| A Supervised Locality Preserving Projection Algorithm for Dimensionality Reduction |
| SHEN ZhongHua, PAN YongHui, WANG ShiTong |
| School of Information Technology, Southern Yangtze University, Wuxi 214122 |
|
|
|
|
Abstract Aiming at the unsupervised property of locality preserving projection (LPP), a linear dimensionality reduction method called supervised locality preserving projections (SLPP) is proposed, which integrates the locality preserving property in LPP and the class separability. Experimental results show SLPP is superior to some classical and recently presented methods. The linear SLPP method can also be extended to nonlinear dimensionality reduction scenarios by using the kernel method.
|
|
Received: 15 December 2006
|
|
|
|
|
|
[1] Tenenbaum J B, de Silva V, Langford J C. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 2000, 290(5500): 23192323
[2] Roweis S T, Saul L K. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science, 2000, 290(5500): 23232326
[3] He Xiaofen, Niyogi P. Locality Preserving Projections // Thrun S, Saul L K, Schlkopf B, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 2004, 16: 153160
[4] Jolloffe I T. Principal Component Analysis. New York, USA: SpringerVerlag, 1986
[5] Fisher R A. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics, 1936, 7(2): 179188
[6] Fukunaga K. Introduction to Statistical Pattern Recognition. 2nd Edition. Boston, USA: Academic Press, 1990
[7] Sugiyama M. Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction // Proc of the 23rd International Conference on Machine Learning. Pittsburgh, USA, 2006: 905912
[8] Belkin M, Niyogi P. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering // Dietterich T G, Becker S, Ghahramani Z, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 2001, 14: 585591
[9] Vapnik V N. Statistical Learning Theory. New York, USA: Wiley, 1998
[10] Schlkopf B, Smola A J, Müller K R. Nonlinear Component Analysis as a Kernel Eigenvalue Problem. Neural Computation, 1998, 10(5): 12991319
[11] ZelnikManor L, Person P. SelfTuning Spectral Clustering // Saul L K, Weiss Y, Bottou L, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 2005, 17: 16011608
[12] Asuncion A, Newman D J. UCI Repository of Machine Learning Databases [DB/OL]. [20070101]. http://www.ics.uci.edu/~mlearn/MLRepository.html
[13] Schlkopf B, Smola A J. Learning with Kernels: Support Vector Machines Regularization, Optimization and Beyond. Cambridge, USA: MIT Press, 2002
[14] He Xiaofei, Yan Shucheng, Hu Yuxiao, et al. Face Recognition Using Laplacianfaces. IEEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27(3): 328340
[15] He Xiaofei, Cai Deng, Yan Shucheng, et al. Neighborhood Preserving Embedding // Proc of the IEEE International Conference on Computer Vision. Beijing, China, 2005, Ⅱ: 12081213 |
|
|
|
2008, Vol. 21 
