nroKohonen: Self-organizing map

Description

Interpolates the initial district profiles of a self-organizing map based on pre-determined seed profiles.

Usage

nroKohonen(seeds, radius = 3)

Arguments

seeds

A matrix or a data frame of K rows and N columns.

radius

Map radius.

Value

A list containing three named elements: centroids contains the N-dimensional district profiles, and topology is an H x 6 matrix that contains the 2D spatial layout for the map districts: the first two columns (X, Y) indicate the positions of districts in Cartesian coordinates, the other four columns (RADIUS1, RADIUS2, ANGLE1, ANGLE2) define the perimeter of the district areas for visualisation on a circular map.

The function is named after Teuvo Kohonen, the inventor of the self-organizing map.

References

Gao S, Mutter S, Casey AE, M<U+00E4>kinen V-P (2018) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, https://doi.org/10.1093/ije/dyy113

Examples

Run this code

# NOT RUN {
# Import data.
fname <- system.file("extdata", "finndiane.txt", package = "Numero")
dataset <- read.delim(file = fname)

# Prepare training data.
trvars <- c("CHOL", "HDL2C", "TG", "CREAT", "uALB")
trdata <- scale.default(dataset[,trvars]) 

# K-means clustering.
km <- nroKmeans(data = trdata)

# Self-organizing map.
sm <- nroKohonen(seeds = km)
print(head(sm$centroids))
print(head(sm$topology))
# }