som {GeneSOM}R Documentation

Function to train a Self-Organizing Map

Description

Produces an object of class "som" which is a Self-Organizing Map fit of the data.

Usage

som(data, xdim, ydim, init="linear", alpha=NULL, alphaType="inverse", neigh="gaussian", topol="rect", radius=NULL, rlen=NULL)

Arguments

data a data frame or matrix of input data.
xdim an integer specifying the x-dimension of the map.
ydim an integer specifying the y-dimension of the map.
init a character string specifying the initializing method. The following are permitted: "sample" uses a radom sample from the data; "random" uses random draws from N(0,1); "linear" uses the linear grids upon the first two principle components directin.
alpha a vector of initial learning rate parameter for the two training phases. Decreases linearly to zero during training.
alphaType a character string specifying learning rate funciton type. Possible choices are linear function ("linear") and inverse-time type function ("inverse").
neigh a character string specifying the neighborhood function type. The following are permitted:
"bubble" "gaussian"
topol a character string specifying the topology type when measuring distance in the map. The following are permitted:
"hexa" "rect"
radius a vector of initial radius of the training area in som-algorithm for the two training phases. Decreases linearly to one during training.
rlen a vector of running length (number of steps) in the two training phases.

Value

An object of class "som" representing the fit.

Author(s)

Jun Yan <jyan@stat.wisc.edu>

See Also

glm, lm, formula.

Examples

data(yeast)
yeast <- yeast[, -c(1, 11)]
yeast.f <- filtering(yeast)
yeast.f.n <- normalize(yeast.f)
foo <- som(yeast.f.n, xdim=5, ydim=6)
foo <- som(yeast.f.n, xdim=5, ydim=6, topol="hexa", neigh="gaussian")