R: Self-Organizing Maps: Online Algorithm

SOM {class} | R Documentation

## Self-Organizing Maps: Online Algorithm

### Description

Kohonen's Self-Organizing Maps are a crude form of multidimensional scaling.

### Usage

    SOM(data, grid = somgrid(), rlen = 10000, alpha, radii, init)

### Arguments

`data` | a matrix or data frame of observations, scaled so that Euclidean distance is appropriate.
`grid` | A grid for the representatives: see `somgrid`.
`rlen` | the number of updates: used only in the defaults for `alpha` and `radii`.
`alpha` | the amount of change: one update is done for each element of `alpha`. Default is to decline linearly from 0.05 to 0 over `rlen` updates.
`radii` | the radii of the neighbourhood to be used for each update: must be the same length as `alpha`. Default is to decline linearly from 4 to 1 over `rlen` updates.
`init` | the initial representatives. If missing, chosen (without replacement) randomly from `data`.

### Details

`alpha` and `radii` can also be lists, in which case each component is used in turn, allowing two- or more phase training.

### Value

An object of class `"SOM"` with components

`grid` | the grid, an object of class `"somgrid"`.
`codes` | a matrix of representatives.

### References

Kohonen, T. (1995) Self-Organizing Maps. Springer-Verlag

Kohonen, T., Hynninen, J., Kangas, J. and Laaksonen, J. (1996) SOM PAK: The self-organizing map program package. Laboratory of Computer and Information Science, Helsinki University of Technology, Technical Report A31.

Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

### See Also

`somgrid`, `batchSOM`

### Examples

    require(graphics)
    data(crabs, package = "MASS")

    lcrabs <- log(crabs[, 4:8])
    crabs.grp <- factor(c("B", "b", "O", "o")[rep(1:4, rep(50,4))])
    gr <- somgrid(topo = "hexagonal")
    crabs.som <- SOM(lcrabs, gr)
    plot(crabs.som)

    ## 2-phase training
    crabs.som2 <- SOM(lcrabs, gr,
        alpha = list(seq(0.05, 0, len = 1e4), seq(0.02, 0, len = 1e5)),
        radii = list(seq(8, 1, len = 1e4), seq(4, 1, len = 1e5)))
    plot(crabs.som2)

[Package class version 7.3-11 Index]