Stability of a Self-Organizing Map

Fits a self-organizing map with som() on resampled data several times, maps all the spectra on each map, and measures how consistently the spectra keep their neighbors.

Usage

som_stability(x, runs = 10, ...)

Arguments

x

A numeric matrix or data frame of spectra, one per row.

runs

The number of resampled fits. Default is 10.

...

Further arguments passed to som(), such as grid or robust.

Value

A list with runs, a tibble with the quantization and topographic errors of each run, stability, the mean correlation between the runs, and correlations, the matrix of the correlations between runs.

Details

Each run fits the map on a bootstrap sample of the spectra (with the same grid), and maps all of them. For each run, the grid distances between the units of every pair of spectra form a matrix; the stability is the mean correlation between these matrices over the pairs of runs. Values close to 1 mean that the same spectra are neighbors on every map, whatever the sample: the structure of the map is not an artifact of the training data. Low values suggest a smaller grid, a larger final radius or more epochs.

See also

som()

Examples

# \donttest{
data(forageLIBS)
# the 380-430 nm window (Ca II H and K lines), faster than all the channels
wl <- suppressWarnings(as.numeric(names(forageLIBS)))
spectra <- forageLIBS[which(wl > 380 & wl < 430)]
set.seed(1)
som_stability(spectra, runs = 5)$stability
#> [1] 0.9546112
# }