Distributed Recursive Graph Layout

Description

An S4 Class implementing Distributed recursive Graph Layout.

Details

DrL uses a complex algorithm to avoid local minima in the graph embedding which uses several steps.

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

DrL can take the following parameters:

ndim

The number of dimensions, defaults to 2. Can only be 2 or 3

knn

Reduce the graph to keep only the neares neighbors. Defaults to 100.

d

The distance function to determine the weights of the graph edges. Defaults to euclidean distances.

Implementation

Wraps around layout_with_drl. The parameters maxiter, epsilon and kkconst are set to the default values and cannot be set, this may change in a future release. The DimRed Package adds an extra sparsity parameter by constructing a knn graph which also may improve visualization quality.

See Also

Other dimensionality reduction methods: DRR-class, DiffusionMaps-class, FastICA-class, FruchtermanReingold-class, HLLE-class, Isomap-class, KamadaKawai-class, LLE-class, MDS-class, PCA-class, dimRedMethod-class, kPCA-class, nMDS-class, tSNE-class

Examples

## Not run: 
dat <- loadDataSet("Swiss Roll", n = 500)

## use the S4 Class directly:
drl <- DrL()
emb <- drl@fun(dat, drl@stdpars)

## simpler, use embed():
emb2 <- embed(dat, "DrL")


plot(emb)

## End(Not run)