SOM: Build a self-organizing map

Description Usage Arguments Value References See Also

Description

Build a self-organizing map

Usage

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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
)

Arguments

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

Value

A list containing all parameter settings and results

References

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

See Also

BuildSOM


FlowSOM documentation built on Nov. 8, 2020, 6:40 p.m.