| protoDist {SOMbrero} | R Documentation |
Compute distances between prototypes
Description
Compute distances, either between all prototypes
(mode = "complete") or only between prototypes' neighbours
(mode = "neighbors").
Usage
protoDist(object, mode = c("complete", "neighbors"), radius = 1, ...)
Arguments
object |
a |
mode |
Specifies which distances should be computed (default to
|
radius |
Radius used to fetch the neighbors (default to 1). The distance used to compute the neighbors is the Euclidean distance. |
... |
Not used. |
Details
When mode="complete", distances between all prototypes are
computed. When mode="neighbors", distances are computed only between
the prototypes and their neighbors. If the data were preprocessed during the
SOM training procedure, the distances are computed on the normalized values
of the prototypes.
Value
When mode = "complete", the function returns a square matrix
which dimensions are equal to the product of the grid dimensions.
When mode = "neighbors", the function returns a list which length is
equal to the product of the grid dimensions; the length of each item is equal
to the number of neighbors. Neurons are considered to have 8 neighbors at
most (i.e., two neurons are neighbors if they have an Euclidean
distance smaller than radius. Natural choice for radius is
1 for hexagonal topology and 1 or \sqrt{2} for square
topology (4 and 8 neighbors respectively).
Author(s)
Madalina Olteanu olteanu@ceremade.dauphine.fr
Nathalie Vialaneix nathalie.vialaneix@inrae.fr
See Also
Examples
set.seed(2343)
my.som <- trainSOM(x.data = iris[,1:4], dimension = c(5,5))
protoDist(my.som)