Distributed Recursive Graph Layout
An S4 Class implementing Distributed recursive Graph Layout.
DrL uses a complex algorithm to avoid local minima in the graph embedding which uses several steps.
fun
A function that does the embedding and returns a dimRedResult object.
stdpars
The standard parameters for the function.
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
.
DrL can take the following parameters:
The number of dimensions, defaults to 2. Can only be 2 or 3
Reduce the graph to keep only the neares neighbors. Defaults to 100.
The distance function to determine the weights of the graph edges. Defaults to euclidean distances.
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.
Martin, S., Brown, W.M., Wylie, B.N., 2007. Dr.l: Distributed Recursive (graph) Layout (No. dRl; 002182MLTPL00). Sandia National Laboratories.
Other dimensionality reduction methods: AutoEncoder-class
,
DRR-class
,
DiffusionMaps-class
,
FastICA-class
,
FruchtermanReingold-class
,
HLLE-class
, Isomap-class
,
KamadaKawai-class
, LLE-class
,
MDS-class
, NNMF-class
,
PCA-class
, PCA_L1-class
,
UMAP-class
,
dimRedMethod-class
,
dimRedMethodList
, kPCA-class
,
nMDS-class
, tSNE-class
## Not run: dat <- loadDataSet("Swiss Roll", n = 300) ## 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)
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