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
funA function that does the embedding and returns a dimRedResult object.
stdparsThe 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
if (FALSE) {
if(requireNamespace(c("igraph", "coRanking"), quietly = TRUE)) {
dat <- loadDataSet("Swiss Roll", n = 200)
emb <- embed(dat, "DrL")
plot(emb, type = "2vars")
}
}