kohonen (version 2.0.5)

map.kohonen: Map data to a supervised or unsupervised SOM

Description

Map a data matrix onto a trained SOM.

Usage

## S3 method for class 'kohonen':
map(x, newdata, whatmap = NULL, weights,
            scale.distances = (nmaps > 1), ...)

Arguments

x

A trained supervised or unsupervised SOM obtained from functions som, xyf, or bdk.

newdata

Data matrix, with rows corresponding to objects.

whatmap

For supersom maps: the layers to take into account.

weights

For supersom maps: weights of the layers that are used for mapping.

scale.distances

whether to rescale distances per layer in the case of supersom maps (default): if TRUE the maximal distance of each layer equals one. If the absolute values of the distances per layer should be used, this argument sho

...

Currently ignored.

Value

• A list with elements
• unit.classif
  a vector of units that are closest to the objects in the data matrix.
• dists
  distances (currently only Euclidean distances) of the objects to the units.
• whatmap,weights,scale.distances
  Values used for these arguments.

See Also

predict.kohonen

Examples

data(wines)
set.seed(7)

training <- sample(nrow(wines), 120)
Xtraining <- scale(wines[training, ])
somnet <- som(Xtraining, somgrid(5, 5, "hexagonal"))

mapping <- map(somnet,
               scale(wines[-training, ],
                     center=attr(Xtraining, "scaled:center"),
                     scale=attr(Xtraining, "scaled:scale")))