# A Framework for Dimensionality Reduction

## Documentation for package ‘dimRed’ version 0.2.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A C D E F G H I K L M N P Q R T U misc

dimRed-package | The dimRed package

## -- A --

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

## -- C --

cophenetic_correlation | Method cophenetic_correlation
cophenetic_correlation-method | Method cophenetic_correlation

## -- D --

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

## -- E --

embed | dispatches the different methods for dimensionality reduction
embed-method | dispatches the different methods for dimensionality reduction

## -- F --

FastICA | Independent Component Analysis
FastICA-class | Independent Component Analysis
FruchtermanReingold | Fruchterman Reingold Graph Layout
FruchtermanReingold-class | Fruchterman Reingold Graph Layout

## -- G --

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

## -- H --

HLLE | Hessian Locally Linear Embedding
HLLE-class | Hessian Locally Linear Embedding

## -- I --

installSuggests | getSuggests
inverse | Class "dimRedResult"
inverse-method | Class "dimRedResult"
Isomap | Isomap embedding
Isomap-class | Isomap embedding

## -- K --

KamadaKawai | Graph Embedding via the Kamada Kawai Algorithm
KamadaKawai-class | Graph Embedding via the Kamada Kawai Algorithm
kPCA | Kernel PCA
kPCA-class | Kernel PCA

## -- L --

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

## -- M --

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

## -- N --

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"

## -- P --

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"
print | Method print
print-method | Class "dimRedResult"

## -- Q --

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

## -- R --

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

## -- T --

total_correlation | Method total_correlation
total_correlation-method | Method total_correlation
tSNE | t-Distributed Stochastic Neighborhood Embedding
tSNE-class | t-Distributed Stochastic Neighborhood Embedding

## -- U --

UMAP | Umap embedding
UMAP-class | Umap embedding

## -- misc --

[-method | Class "dimRedData"