Man pages for Rdimtools
Dimension Reduction and Estimation Methods

aux_gensamplesGenerate model-based samples
aux_graphnbdConstruct Nearest-Neighborhood Graph
aux_kernelcovBuild a centered kernel matrix K
aux_pkgstatShow the number of functions for 'Rdimtools'.
aux_preprocessCentering, decorrelating, or whitening of the data
aux_shortestpathFind shortest path using Floyd-Warshall algorithm
estimate_boxcountBox-counting dimension
estimate_correlationCorrelation Dimension
linear_ANMMAverage Neighborhood Margin Maximization
linear_BPCABayesian Principal Component Analysis
linear_CCACanonical Correlation Analysis
linear_DSPPDiscriminative Sparsity Preserving Projection
linear_ESLPPExtended Supervised Locality Preserving Projection
linear_EXTLPPExtended Locality Preserving Projection
linear_FAExploratory Factor Analysis
linear_ICAIndependent Component Analysis
linear_ISOPROJIsometric Projection
linear_KMVPKernel-Weighted Maximum Variance Projection
linear_KUDPKernel-Weighted Unsupervised Discriminant Projection
linear_LDALinear Discriminant Analysis
linear_LDELocal Discriminant Embedding
linear_LEALocally Linear Embedded Eigenspace Analysis
linear_LFDALocal Fisher Discriminant Analysis
linear_LLPLocal Learning Projections
linear_LMDSLandmark Multidimensional Scaling
linear_LPPLocality Preserving Projection
linear_LSPPLocal Similarity Preserving Projection
linear_MDS(Classical) Multidimensional Scaling
linear_MMCMaximum Margin Criterion
linear_MVPMaximum Variance Projection
linear_NPENeighborhood Preserving Embedding
linear_OLPPOrthogonal Locality Preserving Projection
linear_OPLSOrthogonal Partial Least Squares
linear_PCAPrincipal Component Analysis
linear_PLSPartial Least Squares
linear_PPCAProbabilistic Principal Component Analysis
linear_RNDPROJRandom Projection
linear_SDLPPSample-Dependent Locality Preserving Projection
linear_SLPPSupervised Locality Preserving Projection
linear_SPCASparse Principal Component Analysis
linear_SPPSparsity Preserving Projection
linear_UDPUnsupervised Discriminant Projection
nonlinear_CISOMAPConformal Isometric Feature Mapping
nonlinear_CRCACurvilinear Component Analysis
nonlinear_CRDACurvilinear Distance Analysis
nonlinear_DMDiffusion Maps
nonlinear_ISOMAPIsometric Feature Mapping
nonlinear_ISPEIsometric Stochastic Proximity Embedding
nonlinear_KECAKernel Entropy Component Analysis
nonlinear_KLDEKernel Local Discriminant Embedding
nonlinear_KLFDAKernel Local Fisher Discriminant Analysis
nonlinear_KMMCKernel Maximum Margin Criterion
nonlinear_KPCAKernel Principal Component Analysis
nonlinear_LAPEIGLaplacian Eigenmaps
nonlinear_LISOMAPLandmark Isometric Feature Mapping
nonlinear_LLELocally-Linear Embedding
nonlinear_LTSALocal Tangent Space Alignment
nonlinear_MVEMinimum Volume Embedding
nonlinear_MVUMaximum Variance Unfolding / Semidefinite Embedding
nonlinear_PLPPiecewise Laplacian-based Projection (PLP)
nonlinear_REERobust Euclidean Embedding
nonlinear_RPCARobust Principal Component Analysis
nonlinear_SAMMONSammon Mapping
nonlinear_SNEStochastic Neighbor Embedding
nonlinear_SPEStochastic Proximity Embedding
nonlinear_TSNEt-distributed Stochastic Neighbor Embedding
oos_LINEAROut-of-sample prediction for linear methods
RdimtoolsDimension Reduction and Estimation Methods
Rdimtools documentation built on Jan. 3, 2018, 1:04 a.m.