Mini-batch k-means clustering — rs_k_means_mini

Rust interface for mini-batch k-means clustering (Sculley 2010). Uses random mini-batches with a decaying learning rate for faster convergence on large data sets.

Usage

rs_k_means_mini_batch(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).