If you ask for two outputs, you obtain.
You may observe this behavior in most techniques that are based on neighborhood graphs.M as well as constructW.MathWorks does not warrant, and disclaims all liability for, the accuracy, suitability, or fitness for purpose of the translation.ConstructW : Function used to construct the affinity matrix.deng Cai, Xiaofei He and Jiawei Han, "Spectral Regression for Efficient concour caplp externe Regularized Subspace Learning iccv'07.This function will be called by KernelLPP.deng Cai, Xiaofei He and Jiawei Han, "srda: An Efficient Algorithm for Large-Scale Discriminant Analysis ieee tkde 2008.Bibtex source LPP : Locality Preserving Projection (You need to download LGE.Parametric techniques are typically not well suited for visualization, because they constrain the mapping between the data and the visualization.Bibtex source IsoProjection : Isometric Projection (You need to download LGE.Back-projection can only be implemented for linear techniques, for autoencoders, and for the gplvm.Bibtex source MMP : Maximum Margin Projection Xiaofei He, Deng Cai, Jiawei Han, "Learning a Maximum Margin Subspace for Image Retrieval tkde 2008 Bibtex source GenSpatialSmoothRegularizer code promo sony : Generate the spatially smooth regularizer Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han cadeau marraine pour sa filleule and Thomas Huang, "Learning.Bibtex source, deng Cai, Xiaofei He, Jiawei Han, "Speed Up Kernel Discriminant Analysis The vldb Journal, 2011.FAQ When using the toolbox, the code quits saying that some function could not be found?Local Linear Coordination (LLC manifold charting, coordinated Factor Analysis (CFA).MySVD : An efficient SVD.
This function will be called by TensorLPP.
If you type help pca you will see loads of information about the function.

Isomap/LLE/Laplacian Eigenmaps/ltsa can only embed data that gives rise to a connected neighborhood graph.
Maximum Variance Unfolding (extension of LLE).
PDF Supplemental material Talk Download Please click here to download the toolbox.