daltoolbox (version 1.2.747)

cluster_kmeans: k-means

Description

k-means clustering using stats::kmeans.

Usage

cluster_kmeans(k = 1)

Value

returns a k-means object.

Arguments

k

the number of clusters to form.

Details

Partitions data into k clusters minimizing within‑cluster sum of squares. The intrinsic quality metric returned is the total within‑cluster SSE (lower is better).

References

MacQueen, J. (1967). Some Methods for classification and Analysis of Multivariate Observations. Lloyd, S. (1982). Least squares quantization in PCM.

Examples

# setup clustering
model <- cluster_kmeans(k=3)

#load dataset
data(iris)

# build model
model <- fit(model, iris[,1:4])
clu <- cluster(model, iris[,1:4])
table(clu)

# evaluate model using external metric
eval <- evaluate(model, clu, iris$Species)
eval