Generate clustered synthetic data

Separated Gaussian clusters, with a fifth of the points on thin bridges between neighbouring clusters so the boundaries aren't trivially clean. The baseline of the four generators.

All generators are the ones behind the Rust crate's benchmark tables. They draw in f32 like the crate's gridsearch examples and the Python bindings, so the same seed gives the same points in all three.

Usage

generate_clustered_data(n, dim, n_clusters = 25L, seed = 42L)

Arguments

n

Integer. Number of samples.

dim

Integer. Number of features.

n_clusters

Integer. Number of clusters.

seed

Integer. Random seed.

Value

A list with:

• data - Numeric matrix, n x dim.

• labels - Integer vector of 1-based cluster labels.

Examples

dat <- generate_clustered_data(1000L, 16L, n_clusters = 5L)
table(dat$labels)
#> 
#>   1   2   3   4   5 
#> 172 133 168 243 284