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Tidy K-Means Clustering

Source: R/unsupervised-clustering.R
tidy_kmeans.Rd

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 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)