k_means: K-Means

In tidyclust: A Common API to Clustering

K-Means

Description

k_means() defines a model that fits clusters based on distances to a number of centers.

Usage

k_means(mode = "partition", engine = "stats", num_clusters = NULL)

Arguments

mode	A single character string for the type of model. The only possible value for this model is "partition".
engine	A single character string specifying what computational engine to use for fitting. Possible engines are listed below. The default for this model is "stats".
num_clusters	Positive integer, number of clusters in model.

Value

A k_means cluster specification.

Examples

# Show all engines
modelenv::get_from_env("k_means")

k_means()

tidyclust documentation built on March 7, 2023, 8:38 p.m.