A C D E F G H I K L M N P Q R T U misc
| dimRed-package | The dimRed package |
| as.data.frame | Converts to data.frame |
| as.data.frame-method | Class "dimRedData" |
| as.data.frame-method | Class "dimRedResult" |
| as.dimRedData | Converts to dimRedData |
| as.dimRedData-method | Converts to dimRedData |
| AUC_lnK_R_NX | Method AUC_lnK_R_NX |
| AUC_lnK_R_NX-method | Method AUC_lnK_R_NX |
| AutoEncoder | AutoEncoder |
| AutoEncoder-class | AutoEncoder |
| cophenetic_correlation | Method cophenetic_correlation |
| cophenetic_correlation-method | Method cophenetic_correlation |
| dataSetList | Example Data Sets for dimensionality reduction |
| dataSets | Example Data Sets for dimensionality reduction |
| DiffusionMaps | Diffusion Maps |
| DiffusionMaps-class | Diffusion Maps |
| dimRed | The dimRed package |
| dimRedData | Class "dimRedData" |
| dimRedData-class | Class "dimRedData" |
| dimRedMethod-class | Class "dimRedMethod" |
| dimRedMethodList | dimRedMethodList |
| dimRedQualityList | Quality Criteria for dimensionality reduction. |
| dimRedResult | Class "dimRedResult" |
| dimRedResult-class | Class "dimRedResult" |
| distance_correlation | Method distance_correlation |
| distance_correlation-method | Method distance_correlation |
| DrL | Distributed Recursive Graph Layout |
| DrL-class | Distributed Recursive Graph Layout |
| DRR | Dimensionality Reduction via Regression |
| DRR-class | Dimensionality Reduction via Regression |
| embed | dispatches the different methods for dimensionality reduction |
| embed-method | dispatches the different methods for dimensionality reduction |
| FastICA | Independent Component Analysis |
| FastICA-class | Independent Component Analysis |
| FruchtermanReingold | Fruchterman Reingold Graph Layout |
| FruchtermanReingold-class | Fruchterman Reingold Graph Layout |
| getData | Method getData |
| getData-method | Class "dimRedData" |
| getDimRedData | Method getDimRedData |
| getDimRedData-method | Class "dimRedResult" |
| getMeta | Method getMeta |
| getMeta-method | Class "dimRedData" |
| getNDim | Method getNDim |
| getNDim-method | Class "dimRedResult" |
| getOrgData | Method getOrgData |
| getOrgData-method | Class "dimRedResult" |
| getOtherData | Method getOtherData |
| getOtherData-method | Class "dimRedResult" |
| getPars | Method getPars |
| getPars-method | Class "dimRedResult" |
| getRotationMatrix | getRotationMatrix |
| HLLE | Hessian Locally Linear Embedding |
| HLLE-class | Hessian Locally Linear Embedding |
| installSuggests | getSuggests |
| inverse | Class "dimRedResult" |
| inverse-method | Class "dimRedResult" |
| Isomap | Isomap embedding |
| Isomap-class | Isomap embedding |
| KamadaKawai | Graph Embedding via the Kamada Kawai Algorithm |
| KamadaKawai-class | Graph Embedding via the Kamada Kawai Algorithm |
| kPCA | Kernel PCA |
| kPCA-class | Kernel PCA |
| LaplacianEigenmaps | Laplacian Eigenmaps |
| LaplacianEigenmaps-class | Laplacian Eigenmaps |
| LCMC | Method LCMC |
| LCMC-method | Method LCMC |
| LLE | Locally Linear Embedding |
| LLE-class | Locally Linear Embedding |
| loadDataSet | Example Data Sets for dimensionality reduction |
| makeKNNgraph | makeKNNgraph |
| maximize_correlation | Maximize Correlation with the Axes |
| maximize_correlation-method | Maximize Correlation with the Axes |
| MDS | Metric Dimensional Scaling |
| MDS-class | Metric Dimensional Scaling |
| mean_R_NX | Method mean_R_NX |
| mean_R_NX-method | Method mean_R_NX |
| mixColor1Ramps | Mixing color ramps |
| mixColor2Ramps | Mixing color ramps |
| mixColor3Ramps | Mixing color ramps |
| mixColorRamps | Mixing color ramps |
| ndims | Method ndims |
| ndims-method | Class "dimRedData" |
| ndims-method | Class "dimRedResult" |
| nMDS | Non-Metric Dimensional Scaling |
| nMDS-class | Non-Metric Dimensional Scaling |
| NNMF | Non-Negative Matrix Factorization |
| NNMF-class | Non-Negative Matrix Factorization |
| nrow-method | Class "dimRedData" |
| PCA | Principal Component Analysis |
| PCA-class | Principal Component Analysis |
| PCA_L1 | Principal Component Analysis with L1 error. |
| PCA_L1-class | Principal Component Analysis with L1 error. |
| plot | Plotting of dimRed* objects |
| plot-method | Plotting of dimRed* objects |
| plot.dimRed | Plotting of dimRed* objects |
| plot.dimRedData | Plotting of dimRed* objects |
| plot.dimRedResult | Plotting of dimRed* objects |
| plot_R_NX | plot_R_NX |
| predict-method | Class "dimRedResult" |
| Method print | |
| print-method | Class "dimRedResult" |
| quality | Quality Criteria for dimensionality reduction. |
| quality-method | Quality Criteria for dimensionality reduction. |
| quality.dimRedResult | Quality Criteria for dimensionality reduction. |
| Q_global | Method Q_global |
| Q_global-method | Method Q_global |
| Q_local | Method Q_local |
| Q_local-method | Method Q_local |
| Q_NX | Method Q_NX |
| Q_NX-method | Method Q_NX |
| reconstruction_error | Method reconstruction_error |
| reconstruction_error-method | Method reconstruction_error |
| reconstruction_rmse | Method reconstruction_rmse |
| reconstruction_rmse-method | Method reconstruction_rmse |
| R_NX | Method R_NX |
| R_NX-method | Method R_NX |
| total_correlation | Method total_correlation |
| total_correlation-method | Method total_correlation |
| tSNE | t-Distributed Stochastic Neighborhood Embedding |
| tSNE-class | t-Distributed Stochastic Neighborhood Embedding |
| UMAP | Umap embedding |
| UMAP-class | Umap embedding |
| [-method | Class "dimRedData" |