xyf
maps to multiple data layers, possibly with
different numbers of variables (though equal numbers of objects). NAs
are allowed (see below). A weighted distance over all layers is
calculated to determine the winning units during training.supersom(data, grid=somgrid(), rlen = 100, alpha = c(0.05, 0.01),
radius = quantile(nhbrdist, 0.67) * c(1, -1),
contin, toroidal = FALSE, n.hood, whatmap = NULL, weights = 1,
maxNA.fraction = .5, keep.data = TRUE)
somgrid
.rlen
updates.contin
is FALSE
.supersom
maps: what layers to use in the
mapping.keep.data == TRUE
.data
are continuous or categorical.keep.data == TRUE
.keep.data == TRUE
.somgrid
.supersom
maps: weights of layers uses in the
mapping.supersom
maps: what layers to use in the
mapping.somgrid
, plot.kohonen
data(yeast)
yeast.supersom <- supersom(yeast, somgrid(6, 6, "hexagonal"), whatmap = 3:6)
obj.classes <- as.integer(yeast$class)
colors <- c("yellow", "green", "blue", "red", "orange")
plot(yeast.supersom, type = "mapping", col = colors[obj.classes],
pch = obj.classes, main = "yeast data", keepMargins = TRUE)
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