SOM {FlowSOM} | R Documentation |
Build a self-organizing map
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, initf = Initialize_KWSP, distf = 2, silent = FALSE, codes = NULL, importance = NULL )
data |
Matrix containing the training data |
xdim |
Width of the grid |
ydim |
Hight of the grid |
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 |
initf |
Use the given initialization function if init == T (default: Initialize_KWSP) |
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 |
A list containing all parameter settings and results
This code is strongly based on the kohonen
package.
R. Wehrens and L.M.C. Buydens, Self- and Super-organising Maps
in R: the kohonen package J. Stat. Softw., 21(5), 2007