R: Distributed Recursive Graph Layout

DrL-class {dimRed} | R Documentation

## 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)

[Package dimRed version 0.1.0 Index]