Usage
SOM(data, xdim = 10, ydim = 10, rlen = 10, mst = 1, alpha = c(0.05, 0.01), radius = stats::quantile(nhbrdist, 0.67) * c(1, 0), init = FALSE, distf = 2, silent = FALSE, codes = NULL, importance = NULL)
Arguments
data
Matrix containing the training data
rlen
Number of times to loop over the training data for each MST
mst
Number of times to build an MST
alpha
Start and end learning rate
radius
Start and end radius
init
Initialize cluster centers in a non-random way
distf
Distance function (1=manhattan, 2=euclidean, 3=chebyshev,
4=cosine)
silent
If FALSE, print status updates
codes
Cluster centers to start with
importance
array with numeric values. Parameters will be scaled
according to importance