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K-means clustering (full)

rs_k_means.Rd

[Experimental] Rust interface for k-means clustering using Lloyd's algorithm with SIMD or GEMM acceleration depending on dimensionality. It exposes the high performance k-means clustering code from the Rust crate ann-search-rs for rapid clustering.

Usage

rs_k_means(data, k, kmeans_params, seed, verbose)

Arguments

data

Numerical matrix. The data to cluster, of dimensions samples x features.

k

Integer. Number of clusters.

kmeans_params

Named list. Parameters produced by params_kmeans().

seed

Integer. Seed for reproducibility.

verbose

Boolean. Controls verbosity.

Value

A named list with:

  • centroids - Numeric matrix of shape k x features.

  • assignments - Integer vector of length samples (1-indexed).