GPU-accelerated k-means clustering

Performs k-means clustering as a GPU-accelerated form. In its current form uses the cubecl with wgpu backend.

Usage

k_means_cluster_gpu(
  data,
  k,
  kmeans_params = params_kmeans_gpu(),
  seed = 42L,
  .verbose = TRUE
)

Arguments

data

Numerical matrix or data frame. The data to cluster, of shape samples x features. Will be coerced to a matrix.

k

Integer. Number of clusters to create. Must be >= 2.

kmeans_params

Named list. GPU-accelerated k-mean parameters, see params_kmeans_gpu().

seed

Integer. Random seed for reproducibility. Defaults to 42L.

.verbose

Logical. Controls verbosity. Defaults to TRUE.

Value

A KMeansClusterGPU class with assignments and centroids.