tidy_kmeans: Tidy K-Means Clustering

In tidylearn: A Unified Tidy Interface to R's Machine Learning Ecosystem

Tidy K-Means Clustering

Description

Performs k-means clustering with tidy output

Usage

tidy_kmeans(
  data,
  k,
  cols = NULL,
  nstart = 25,
  iter_max = 100,
  algorithm = "Hartigan-Wong"
)

Arguments

data	A data frame or tibble
k	Number of clusters
cols	Columns to include (tidy select). If NULL, uses all numeric columns.
nstart	Number of random starts (default: 25)
iter_max	Maximum number of iterations (default: 100)
algorithm	K-means algorithm: "Hartigan-Wong" (default), "Lloyd", "Forgy", "MacQueen"

Value

A list of class "tidy_kmeans" containing:

• clusters: tibble with observation IDs and cluster assignments

• centers: tibble of cluster centers

• metrics: tibble with clustering quality metrics

• model: original kmeans object

Examples

# Basic k-means
km_result <- tidy_kmeans(iris, k = 3)

tidylearn documentation built on Feb. 6, 2026, 5:07 p.m.