som.nn.som.experimental: Work hourse for som training.

In som.nn: Topological k-NN Classifier Based on Self-Organising Maps

Work hourse for som training.

Description

Function is the kernel internal for som training, implemented in pure R.

Usage

som.nn.som.experimental(
  data,
  grid,
  len = 100,
  alpha = 0.05,
  radius,
  init,
  toroidal = FALSE
)

Arguments

data	matrix with training data.
grid	somgrid object
len	number of steps to be trained (steps - not epochs!).
alpha	learning rate c(first, last).
radius	radius c(first, last).
init	codes for initialisation.
toroidal	true if doughnut-shaped som.

Value

    S3 object of type \code{kohonen} with the trained som.

som.nn documentation built on May 29, 2024, 6:50 a.m.