CAMACHO J,PIC J,FERRER A.Data understanding with PCA: Structural and variance information plots[J].Chemometrics and Intelligent Laboratory Systems,2010,100(1):48-56.
[5]
LIPOVETSKY S.PCA and SVD with nonnegative loadings[J].Pattern Recognition,2009,42(1):68-76.
[6]
LEE D D,SEUNG H S.Learning the parts of objects by non-negative matrix factorization[J].Nature,1999,401(6755):788-791.
[7]
RADULOVIC J,RANKOVIC V.Feedforward neural network and adaptive network-based fuzzy inference system in study of power lines[J].Expert Systems with Applications,2010,37(1):165-170.
[8]
PETER N B,JOAO P H,DAVID J K,et al.Fisherfaces: Recognition using class specific linear projection[J].IEEE Trans on Pattern Analysis and Machine Intelligence,1997,19(7):711-720.
[9]
HSUAN Y M.Kernel eigenfaces vs kernel fisherfaces: Face recognition using kernel methods[C]//Processing of the 5th IEEE International Conference on Automatic Face and Gesture Recognition.Washington D C:IEEE Press,2002:215-220.
ROWEIS S T,SAUL L K.Nonlinear dimensionality reduction by locally linear embedding[J].Science,2000,290(5500):2323-2326.
[12]
HE Xiao-feng,NIYOGI P.Locality preserving projections[C]//Advances in Neural Information Processing Systems.Vancouver:[s.n.],2003:153-160.
[13]
LOPEZ M M,RAMIREZ J,ALVAREZ I,et al.SVM-based CAD system for early detection of the Alzheimer’s disease using kernel PCA and LDA[J].Neuroscience Letters,2009,464(3):233-238.
[14]
MIKA S,RATSCH G,WESTON J,et al.Constructing descriptive and discriminative nonlinear features: Rayleigh coefficients in kernel feature spaces[J].Pattern Analysis and Machine Intelligence,2003,25(5):623-628.
[15]
BELKIN M,NIYOGI P.Laplacian eigenmaps and spectral techniques for embedding and clustering[C]//Processing of Advances in Neural Information Processing Systems.Cambridge:MIT Press,2001:585-591.
