dimRed (version 0.2.5)

LLE-class: Locally Linear Embedding

Description

An S4 Class implementing Locally Linear Embedding (LLE)

Slots

fun

A function that does the embedding and returns a dimRedResult object.

stdpars

The standard parameters for the function.

General usage

Dimensionality reduction methods are S4 Classes that either be used directly, in which case they have to be initialized and a full list with parameters has to be handed to the @fun() slot, or the method name be passed to the embed function and parameters can be given to the ..., in which case missing parameters will be replaced by the ones in the @stdpars.

Parameters

LLE can take the following parameters:

knn

the number of neighbors for the knn graph., defaults to 50.

ndim

the number of embedding dimensions, defaults to 2.

Implementation

Wraps around lle, only exposes the parameters k and m.

Details

LLE approximates the points in the manifold by linear combination of its neighbors. These linear combinations are the same inside the manifold and in highdimensional space.

References

Roweis, S.T., Saul, L.K., 2000. Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science 290, 2323-2326. doi:10.1126/science.290.5500.2323

See Also

Other dimensionality reduction methods: AutoEncoder-class, DRR-class, DiffusionMaps-class, DrL-class, FastICA-class, FruchtermanReingold-class, HLLE-class, Isomap-class, KamadaKawai-class, MDS-class, NNMF-class, PCA-class, PCA_L1-class, UMAP-class, dimRedMethod-class, dimRedMethodList(), kPCA-class, nMDS-class, tSNE-class

Examples

dat <- loadDataSet("3D S Curve", n = 500)
emb <- embed(dat, "LLE", knn = 45)
plot(emb, type = "2vars")