batchSOM {class} | R Documentation |
Kohonen's Self-Organizing Maps are a crude form of multidimensional scaling.
batchSOM(data, grid = somgrid(), radii, init) somgrid(xdim = 8, ydim = 6, topo = c("rectangular", "hexagonal"))
data |
a matrix or data frame of observations, scaled so that Euclidean distance is appropriate. |
grid |
A grid for the representatives. |
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 .
|
xdim, ydim |
dimensions of the grid |
topo |
the topology of the grid. |
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) Self-Organizing Maps. Springer-Verlag
library(MASS) library(mva) # for dist 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))