Computer Science ›› 2015, Vol. 42 ›› Issue (2): 256-259,295.doi: 10.11896/j.issn.1002-137X.2015.02.053

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Dimensionality Reduction Algorithm Based on Neighborhood Rival Linear Embedding

LI Yan-yan and YAN De-qin   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In order to improve the correctness of locally linear embedding caused by sparse data,a novel dimensionality reduction algorithm based on neighborhood rival linear embedding was proposed in this paper.According to the statistical information,it determines local linear dynamic range,adopts the cam distribution to find neighbors of data points,and avoids the lack of the direction of neighbor selection.In the case of sparse data sets,the algorithm can effectively obtain local and global information of data.The experiment to test the improved algorithm obtains a good effort of reducing dimension.The experimental results on the image retrieval using the Corel database show the efficiency of the algorithm.

Key words: Linearization,Manifold learning,Locally linear embedding,Sparse,Dimensionality reduction

[1] Jolliffe I.Principal component analysis[M].John Wiley & Sons,Ltd,2005
[2] Cox T,Cox M.Multidimensional Scaling[M].Chapman &Hall,London,UK,2000
[3] Tenenbaum J B,De Silva V,Lagford J C.A global geometricframework for nonlinear dimensionality reduction[J].Science,2000,0(5500):2319-2323
[4] Zhang Z,Zha H.Principal manifolds and nonlinear dimensionali-ty reduction via tangent space alignment[J].Journal of Shanghai University (English Edition),2004,8(4):406-424
[5] Roweis S T,Saul L K.Nonlinear dimensionality reduction by locally linear embedding[J].Science,2000,0(5500):2323-2326
[6] Balasubramanian M,Schwartz E L.The ISOMAP algorithm and topological stability[J].Science,2002,5(5552):7
[7] Silva J G,Marques J S,Lemos J M.Selecting Landmarks Points for Sparse Manifold Learning[C]∥Advances in Neural Information Processing.2006
[8] Ye Qing-wei,Sun Yang.An Improved LLE Algorithm withSparse Constraint[J].Journal of Computational and Theoretical Nanoscience,2013,0(12):2872-2876
[9] Kong De-guang,Ding C.An iterative locally linear embedding algorithm[C]∥Proceedings of the 29th International Confe-rence on Machine Learning,Vol 2,2:1647-1654
[10] Yin Kai.Dimensionality reduction based on sparse representa-tion classifier[J].Journal of Computational Information Systems,2012,8(9):3777-3783 (下转第295页)(上接第259页)
[11] Nguyen,Hien V.Sparse embedding:A framework for sparsity promoting dimensionality reduction[J].Lecture Notes in Computer Science,2012,7(6):414-427
[12] 冷亦琴,张莉,杨季文.一种基于局部稀疏线性嵌入的降维方法及其应用[J].南京大学学报,2013,9(4):403-410
[13] Sun Yang,Ye Qing-wei,Wang Xiao-dong,et al.Improved LLE Algorithm Based on Sparse Constraint[J].Computer Enginee-ring,2013,9(5):53-56,0
[14] 陈才扣,喻以明,史俊.一种快速的基于稀疏表示分类器[J].南京大学学报,2012,48(1):71-76
[15] Pan Y,Ge S S,Mamun A A.Weighted Locally Linear Embedding for Dimension Reduction[J].Pattern Recognition,2009,2(5):798-811

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