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Run the SOM algorithm for clustering.
SOM( d, xdim = floor(sqrt(nrow(d))), ydim = floor(sqrt(nrow(d))), rlen = 10000, post = c("none", "single", "ward"), k = NULL, ... )
The fitted Kohonen's map as an object of class som.
som
The dataset (matrix or data.frame).
matrix
data.frame
The dimensions of the grid.
The number of iterations.
The post-treatement method: "none" (None), "single" (Single link) or "ward" (Ward clustering).
"none"
"single"
"ward"
The number of cluster (only used if post is different from "none").
post
Other parameters.
plot.som, som-class, som
plot.som
som-class
require (datasets) data (iris) SOM (iris [, -5], xdim = 5, ydim = 5, post = "ward", k = 3)
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