kmeans.getk: Estimation of the number of clusters for _K_-means

In fdm2id: Data Mining and R Programming for Beginners

Estimation of the number of clusters for K-means

Description

Estimate the optimal number of cluster of the K-means clustering method.

Usage

kmeans.getk(
  d,
  max = 9,
  criterion = "pseudo-F",
  graph = TRUE,
  nstart = 10,
  seed = NULL
)

Arguments

d	The dataset (matrix or data.frame).
max	The maximum number of clusters. Values from 2 to max are evaluated.
criterion	The criterion to be optimized. "pseudo-F" is the only criterion implemented in the current version.
graph	A logical indicating whether or not a graphic should be plotted.
nstart	The number of random sets chosen for kmeans initialization.
seed	A specified seed for random number generation.

Value

The optimal number of cluster of the K-means clustering method according to the chosen criterion.

See Also

pseudoF, kmeans

Examples

require (datasets)
data (iris)
kmeans.getk (iris [, -5])

fdm2id documentation built on July 9, 2023, 6:05 p.m.