LPcaML                  Local PCA Manifold Learning
RML                     Riemannian Manifold Learning
checkParts              Comparing partitions (clustering)
clustering              Main clustering functions
datacf                  Two artificial data sets
dimension               Dimension estimation
fmetam_1cl              Build and validate the functional outputs model
fperrors                Empirical error estimators
getNI                   Top-level neighborhoods functions
getcoefc                Mixing functional models
gt_cxcomps              Functions around graph conenxity
km_PCA                  k-means like functions
learnClassif            Building a classifier
learnRegress            Statistical learning (regression)
linEmb                  Around orthonormal bases
modelcf                 package modelcf
nlin_redDim             Dimensionality reduction and associate
                        reconstruction
plotC                   Printing and plotting utilitiy functions
predictClassif          Predictions for some models
reordering              Rearrangement of clusters
