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.

### References

Martin, S., Brown, W.M., Wylie, B.N., 2007. Dr.l: Distributed Recursive (graph) Layout (No. dRl; 002182MLTPL00). Sandia National Laboratories.

### See Also

Other dimensionality reduction methods:
`AutoEncoder-class`

,
`DRR-class`

,
`DiffusionMaps-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

```
## Not run:
if(requireNamespace(c("igraph", "coRanking"), quietly = TRUE)) {
dat <- loadDataSet("Swiss Roll", n = 200)
emb <- embed(dat, "DrL")
plot(emb, type = "2vars")
}
## End(Not run)
```

*dimRed*version 0.2.6 Index]