Man pages for Rdimtools
Dimension Reduction and Estimation Methods
| aux_gensamples | Generate model-based samples |
| aux_graphnbd | Construct Nearest-Neighborhood Graph |
| aux_kernelcov | Build a centered kernel matrix K |
| aux_pkgstat | Show the number of functions for 'Rdimtools'. |
| aux_preprocess | Preprocessing the data |
| aux_shortestpath | Find shortest path using Floyd-Warshall algorithm |
| estimate_boxcount | Box-counting Dimension |
| estimate_clustering | Intrinsic Dimension Estimation via Clustering |
| estimate_correlation | Correlation Dimension |
| estimate_danco | Intrinsic Dimensionality Estimation with DANCo |
| estimate_gdistnn | Intrinsic Dimension Estimation based on Manifold Assumption... |
| estimate_incisingball | Intrinsic Dimension Estimation with Incising Ball |
| estimate_made | Manifold-Adaptive Dimension Estimation |
| estimate_mindkl | MiNDkl |
| estimate_mindml | MINDml |
| estimate_mle1 | Maximum Likelihood Esimation with Poisson Process |
| estimate_mle2 | Maximum Likelihood Esimation with Poisson Process and Bias... |
| estimate_nearneighbor1 | Intrinsic Dimension Estimation with Near-Neighbor Information |
| estimate_nearneighbor2 | Near-Neighbor Information with Bias Correction |
| estimate_packing | Intrinsic Dimension Estimation using Packing Numbers |
| estimate_pcathr | PCA Thresholding with Accumulated Variance |
| estimate_twonn | Intrinsic Dimension Estimation by a Minimal Neighborhood... |
| estimate_Ustat | ID Estimation with Convergence Rate of U-statistic on... |
| feature_CSCORE | Constraint Score |
| feature_CSCOREG | Constraint Score using Spectral Graph |
| feature_DISR | Diversity-Induced Self-Representation |
| feature_ENET | Elastic Net Regularization |
| feature_FOSMOD | Forward Orthogonal Search by Maximizing the Overall... |
| feature_FSCORE | Fisher Score |
| feature_LASSO | Least Absolute Shrinkage and Selection Operator |
| feature_LSCORE | Laplacian Score |
| feature_LSDF | Locality Sensitive Discriminant Feature |
| feature_LSLS | Locality Sensitive Laplacian Score |
| feature_LSPE | Locality and Similarity Preserving Embedding |
| feature_MCFS | Multi-Cluster Feature Selection |
| feature_MIFS | Mutual Information for Selecting Features |
| feature_NRSR | Non-convex Regularized Self-Representation |
| feature_PFA | Principal Feature Analysis |
| feature_PROCRUSTES | Feature Selection using PCA and Procrustes Analysis |
| feature_RSR | Regularized Self-Representation |
| feature_SPECS | Supervised Spectral Feature Selection |
| feature_SPECU | Unsupervised Spectral Feature Selection |
| feature_SPUFS | Structure Preserving Unsupervised Feature Selection |
| feature_UDFS | Unsupervised Discriminative Features Selection |
| feature_UGFS | Unsupervised Graph-based Feature Selection |
| feature_UWDFS | Uncorrelated Worst-Case Discriminative Feature Selection |
| feature_WDFS | Worst-Case Discriminative Feature Selection |
| iris | Load Iris data |
| linear_ADR | Adaptive Dimension Reduction |
| linear_AMMC | Adaptive Maximum Margin Criterion |
| linear_ANMM | Average Neighborhood Margin Maximization |
| linear_ASI | Adaptive Subspace Iteration |
| linear_BPCA | Bayesian Principal Component Analysis |
| linear_CCA | Canonical Correlation Analysis |
| linear_CNPE | Complete Neighborhood Preserving Embedding |
| linear_CRP | Collaborative Representation-based Projection |
| linear_DAGDNE | Double-Adjacency Graphs-based Discriminant Neighborhood... |
| linear_DNE | Discriminant Neighborhood Embedding |
| linear_DSPP | Discriminative Sparsity Preserving Projection |
| linear_ELDE | Exponential Local Discriminant Embedding |
| linear_ELPP2 | Enhanced Locality Preserving Projection (2013) |
| linear_ESLPP | Extended Supervised Locality Preserving Projection |
| linear_EXTLPP | Extended Locality Preserving Projection |
| linear_FA | Exploratory Factor Analysis |
| linear_FSSEM | Feature Subset Selection using Expectation-Maximization |
| linear_ICA | Independent Component Analysis |
| linear_ISOPROJ | Isometric Projection |
| linear_KMVP | Kernel-Weighted Maximum Variance Projection |
| linear_KUDP | Kernel-Weighted Unsupervised Discriminant Projection |
| linear_LDA | Linear Discriminant Analysis |
| linear_LDAKM | Combination of LDA and K-means |
| linear_LDE | Local Discriminant Embedding |
| linear_LDP | Locally Discriminating Projection |
| linear_LEA | Locally Linear Embedded Eigenspace Analysis |
| linear_LFDA | Local Fisher Discriminant Analysis |
| linear_LLP | Local Learning Projections |
| linear_LLTSA | Linear Local Tangent Space Alignment |
| linear_LMDS | Landmark Multidimensional Scaling |
| linear_LPCA2006 | Locally Principal Component Analysis by Yang et al. (2006) |
| linear_LPE | Locality Pursuit Embedding |
| linear_LPFDA | Locality Preserving Fisher Discriminant Analysis |
| linear_LPMIP | Locality-Preserved Maximum Information Projection |
| linear_LPP | Locality Preserving Projection |
| linear_LQMI | Linear Quadratic Mutual Information |
| linear_LSDA | Locality Sensitive Discriminant Analysis |
| linear_LSIR | Localized Sliced Inverse Regression |
| linear_LSPP | Local Similarity Preserving Projection |
| linear_MDS | (Classical) Multidimensional Scaling |
| linear_MFA | Marginal Fisher Analysis |
| linear_MLIE | Maximal Local Interclass Embedding |
| linear_MMC | Maximum Margin Criterion |
| linear_MMP | Maximum Margin Projection |
| linear_MMSD | Multiple Maximum Scatter Difference |
| linear_MODP | Modified Orthogonal Discriminant Projection |
| linear_MSD | Maximum Scatter Difference |
| linear_MVP | Maximum Variance Projection |
| linear_NOLPP | Nonnegative Orthogonal Locality Preserving Projection |
| linear_NONPP | Nonnegative Orthogonal Neighborhood Preserving Projections |
| linear_NPCA | Nonnegative Principal Component Analysis |
| linear_NPE | Neighborhood Preserving Embedding |
| linear_ODP | Orthogonal Discriminant Projection |
| linear_OLDA | Orthogonal Linear Discriminant Analysis |
| linear_OLPP | Orthogonal Locality Preserving Projection |
| linear_ONPP | Orthogonal Neighborhood Preserving Projections |
| linear_OPLS | Orthogonal Partial Least Squares |
| linear_PCA | Principal Component Analysis |
| linear_PFLPP | Parameter-Free Locality Preserving Projection |
| linear_PLS | Partial Least Squares |
| linear_PPCA | Probabilistic Principal Component Analysis |
| linear_RLDA | Regularized Linear Discriminant Analysis |
| linear_RNDPROJ | Random Projection |
| linear_RPCAG | Robust Principal Component Analysis via Geometric Median |
| linear_RSIR | Regularized Sliced Inverse Regression |
| linear_SAMMC | Semi-Supervised Adaptive Maximum Margin Criterion |
| linear_SAVE | Sliced Average Variance Estimation |
| linear_SDA | Semi-Supervised Discriminant Analysis |
| linear_SDLPP | Sample-Dependent Locality Preserving Projection |
| linear_SIR | Sliced Inverse Regression |
| linear_SLPE | Supervised Locality Pursuit Embedding |
| linear_SLPP | Supervised Locality Preserving Projection |
| linear_SPC | Supervised Principal Component Analysis |
| linear_SPCA | Sparse Principal Component Analysis |
| linear_SPP | Sparsity Preserving Projection |
| linear_SSLDP | Semi-Supervised Locally Discriminant Projection |
| linear_UDP | Unsupervised Discriminant Projection |
| linear_ULDA | Uncorrelated Linear Discriminant Analysis |
| nonlinear_BMDS | Bayesian Multidimensional Scaling |
| nonlinear_CGE | Constrained Graph Embedding |
| nonlinear_CISOMAP | Conformal Isometric Feature Mapping |
| nonlinear_CRCA | Curvilinear Component Analysis |
| nonlinear_CRDA | Curvilinear Distance Analysis |
| nonlinear_DM | Diffusion Maps |
| nonlinear_DPPCA | Dual Probabilistic Principal Component Analysis |
| nonlinear_DVE | Distinguishing Variance Embedding |
| nonlinear_FastMap | FastMap |
| nonlinear_HYDRA | Hyperbolic Distance Recovery and Approximation |
| nonlinear_IDMAP | Interactive Document Map |
| nonlinear_ILTSA | Improved Local Tangent Space Alignment |
| nonlinear_ISOMAP | Isometric Feature Mapping |
| nonlinear_ISPE | Isometric Stochastic Proximity Embedding |
| nonlinear_KECA | Kernel Entropy Component Analysis |
| nonlinear_KLDE | Kernel Local Discriminant Embedding |
| nonlinear_KLFDA | Kernel Local Fisher Discriminant Analysis |
| nonlinear_KLSDA | Kernel Locality Sensitive Discriminant Analysis |
| nonlinear_KMFA | Kernel Marginal Fisher Analysis |
| nonlinear_KMMC | Kernel Maximum Margin Criterion |
| nonlinear_KPCA | Kernel Principal Component Analysis |
| nonlinear_KQMI | Kernel Quadratic Mutual Information |
| nonlinear_KSDA | Kernel Semi-Supervised Discriminant Analysis |
| nonlinear_LAMP | Local Affine Multidimensional Projection |
| nonlinear_LAPEIG | Laplacian Eigenmaps |
| nonlinear_LISOMAP | Landmark Isometric Feature Mapping |
| nonlinear_LLE | Locally Linear Embedding |
| nonlinear_LLLE | Local Linear Laplacian Eigenmaps |
| nonlinear_LTSA | Local Tangent Space Alignment |
| nonlinear_MMDS | Metric Multidimensional Scaling |
| nonlinear_MVE | Minimum Volume Embedding |
| nonlinear_MVU | Maximum Variance Unfolding / Semidefinite Embedding |
| nonlinear_NNP | Nearest Neighbor Projection |
| nonlinear_PHATE | Potential of Heat Diffusion for Affinity-based Transition... |
| nonlinear_PLP | Piecewise Laplacian-based Projection (PLP) |
| nonlinear_REE | Robust Euclidean Embedding |
| nonlinear_RPCA | Robust Principal Component Analysis |
| nonlinear_SAMMON | Sammon Mapping |
| nonlinear_SNE | Stochastic Neighbor Embedding |
| nonlinear_SPE | Stochastic Proximity Embedding |
| nonlinear_SPLAPEIG | Supervised Laplacian Eigenmaps |
| nonlinear_SPMDS | Spectral Multidimensional Scaling |
| nonlinear_TSNE | t-distributed Stochastic Neighbor Embedding |
| oos_LINPROJ | OOS : Linear Projection |
| usps | Load USPS handwritten digits data |
