batchSOM {class}  R Documentation 
Kohonen's SelfOrganizing Maps are a crude form of multidimensional scaling.
batchSOM(data, grid = somgrid(), radii, init)
data 
a matrix or data frame of observations, scaled so that Euclidean distance is appropriate. 
grid 
A grid for the representatives: see somgrid .

radii 
the radii of the neighbourhood to be used for each pass: one pass is
run for each element of radii .

init 
the initial representatives. If missing, chosen (without replacement)
randomly from data .

The batch SOM algorithm of Kohonen(1995, section 3.14) is used.
an object of class "SOM"
with components
grid 
the grid, an object of class "somgrid" . 
codes 
a matrix of representatives. 
Kohonen, T. (1995) SelfOrganizing Maps. SpringerVerlag.
Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
data(crabs, package = "MASS") lcrabs < log(crabs[, 4:8]) crabs.grp < factor(c("B", "b", "O", "o")[rep(1:4, rep(50,4))]) gr < somgrid(topo = "hexagonal") crabs.som < batchSOM(lcrabs, gr, c(4, 4, 2, 2, 1, 1, 1, 0, 0)) plot(crabs.som) bins < as.numeric(knn1(crabs.som$code, lcrabs, 0:47)) plot(crabs.som$grid, type = "n") symbols(crabs.som$grid$pts[, 1], crabs.som$grid$pts[, 2], circles = rep(0.4, 48), inches = FALSE, add = TRUE) text(crabs.som$grid$pts[bins, ] + rnorm(400, 0, 0.1), as.character(crabs.grp))