A virtual class "dimRedMethod" to serve as a template to implement methods for dimensionality reduction.
Details
Implementations of dimensionality reductions should inherit from this class.
The fun slot should be a function that takes three arguments
- data
An object of class
dimRedData.- pars
A list with the standard parameters.
- keep.org.data
Logical. If the original data should be kept in the output.
and returns an object of class dimRedResult.
The stdpars slot should take a list that contains standard
parameters for the implemented methods.
This way the method can be called by embed(data, "method-name",
...), where ... can be used to to change single parameters.
Slots
funA function that does the embedding.
stdparsA list with the default parameters for the
funslot.requiresA vector with all packages R packages that need to be installed to run the method. In some occasions a method may work without one of the packages. Does not include Python dependencies such as Tensorflow. Used to auto skip tests
See also
Other dimensionality reduction methods:
AutoEncoder-class,
DRR-class,
DiffusionMaps-class,
DrL-class,
FastICA-class,
FruchtermanReingold-class,
HLLE-class,
Isomap-class,
KamadaKawai-class,
MDS-class,
NNMF-class,
PCA-class,
PCA_L1-class,
UMAP-class,
dimRedMethodList(),
kPCA-class,
nMDS-class,
tSNE-class