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_preprocessPreprocessing the data
aux_shortestpathFind shortest path using Floyd-Warshall algorithm
estimate_boxcountBox-counting dimension
estimate_correlationCorrelation Dimension
linear_ADRAdaptive Dimension Reduction
linear_AMMCAdaptive Maximum Margin Criterion
linear_ANMMAverage Neighborhood Margin Maximization
linear_ASIAdaptive Subspace Iteration
linear_BPCABayesian Principal Component Analysis
linear_CCACanonical Correlation Analysis
linear_CNPEComplete Neighborhood Preserving Embedding
linear_CRPCollaborative Representation-based Projection
linear_DAGDNEDouble-Adjacency Graphs-based Discriminant Neighborhood...
linear_DNEDiscriminant Neighborhood Embedding
linear_DSPPDiscriminative Sparsity Preserving Projection
linear_ELDEExponential Local Discriminant Embedding
linear_ELPP2Enhanced Locality Preserving Projection (2013)
linear_ENETElastic Net Regularization
linear_ESLPPExtended Supervised Locality Preserving Projection
linear_EXTLPPExtended Locality Preserving Projection
linear_FAExploratory Factor Analysis
linear_FSCOREFisher Score
linear_ICAIndependent Component Analysis
linear_ISOPROJIsometric Projection
linear_KMVPKernel-Weighted Maximum Variance Projection
linear_KUDPKernel-Weighted Unsupervised Discriminant Projection
linear_LASSOLeast Absolute Shrinkage and Selection Operator
linear_LDALinear Discriminant Analysis
linear_LDAKMCombination of LDA and K-means
linear_LDELocal Discriminant Embedding
linear_LDPLocally Discriminating Projection
linear_LEALocally Linear Embedded Eigenspace Analysis
linear_LFDALocal Fisher Discriminant Analysis
linear_LLPLocal Learning Projections
linear_LLTSALinear Local Tangent Space Alignment
linear_LMDSLandmark Multidimensional Scaling
linear_LPCALocally Principal Component Analysis
linear_LPELocality Pursuit Embedding
linear_LPFDALocality Preserving Fisher Discriminant Analysis
linear_LPMIPLocality-Preserved Maximum Information Projection
linear_LPPLocality Preserving Projection
linear_LQMILinear Quadratic Mutual Information
linear_LSCORELaplacian Score
linear_LSDALocality Sensitive Discriminant Analysis
linear_LSDFLocality Sensitive Discriminant Feature
linear_LSIRLocalized Sliced Inverse Regression
linear_LSPPLocal Similarity Preserving Projection
linear_MCFSMulti-Cluster Feature Selection
linear_MDS(Classical) Multidimensional Scaling
linear_MFAMarginal Fisher Analysis
linear_MLIEMaximal Local Interclass Embedding
linear_MMCMaximum Margin Criterion
linear_MMPMaximum Margin Projection
linear_MMSDMultiple Maximum Scatter Difference
linear_MODPModified Orthogonal Discriminant Projection
linear_MSDMaximum Scatter Difference
linear_MVPMaximum Variance Projection
linear_NOLPPNonnegative Orthogonal Locality Preserving Projection
linear_NONPPNonnegative Orthogonal Neighborhood Preserving Projections
linear_NPCANonnegative Principal Component Analysis
linear_NPENeighborhood Preserving Embedding
linear_ODPOrthogonal Discriminant Projection
linear_OLDAOrthogonal Linear Discriminant Analysis
linear_OLPPOrthogonal Locality Preserving Projection
linear_ONPPOrthogonal Neighborhood Preserving Projections
linear_OPLSOrthogonal Partial Least Squares
linear_PCAPrincipal Component Analysis
linear_PFLPPParameter-Free Locality Preserving Projection
linear_PLSPartial Least Squares
linear_PPCAProbabilistic Principal Component Analysis
linear_rldaRegularized Linear Discriminant Analysis
linear_RNDPROJRandom Projection
linear_RSIRRegularized Sliced Inverse Regression
linear_SAMMCSemi-Supervised Adaptive Maximum Margin Criterion
linear_SAVESliced Average Variance Estimation
linear_SDASemi-Supervised Discriminant Analysis
linear_SDLPPSample-Dependent Locality Preserving Projection
linear_SIRSliced Inverse Regression
linear_SLPESupervised Locality Pursuit Embedding
linear_SLPPSupervised Locality Preserving Projection
linear_SPCASparse Principal Component Analysis
linear_SPPSparsity Preserving Projection
linear_SSLDPSemi-Supervised Locally Discriminant Projection
linear_UDPUnsupervised Discriminant Projection
linear_ULDAUncorrelated Linear Discriminant Analysis
nonlinear_CISOMAPConformal Isometric Feature Mapping
nonlinear_CRCACurvilinear Component Analysis
nonlinear_CRDACurvilinear Distance Analysis
nonlinear_DMDiffusion Maps
nonlinear_DVEDistinguishing Variance Embedding
nonlinear_ILTSAImproved Local Tangent Space Alignment
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_KLSDAKernel Locality Sensitive Discriminant Analysis
nonlinear_KMFAKernel Marginal Fisher Analysis
nonlinear_KMMCKernel Maximum Margin Criterion
nonlinear_KPCAKernel Principal Component Analysis
nonlinear_KQMIKernel Quadratic Mutual Information
nonlinear_KSDAKernel Semi-Supervised Discriminant 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_SPLAPEIGSupervised Laplacian Eigenmaps
nonlinear_TSNEt-distributed Stochastic Neighbor Embedding
oos_LINEAROut-Of-Sample Prediction for Linear Methods
oos_LINPROJOOS : Linear Projection
RdimtoolsDimension Reduction and Estimation Methods
Rdimtools documentation built on March 18, 2018, 2:04 p.m.