kmeans_clust {ICSClust}

k-means clustering

Description

Wrapper for performing k-means clustering from stats::kmeans().

Usage

kmeans_clust(X, k, clusters_only = FALSE, iter.max = 100, nstart = 20, ...)

Arguments

X

a numeric matrix or data frame of the data. It corresponds to the argument x.

k

the number of clusters searched for. It corresponds to the argument centers.

clusters_only

boolean. If TRUE only the partition of the data is returned as a vector. If FALSE the usual output of the kmeans function is returned.

iter.max

the maximum number of iterations allowed.

nstart

if centers is a number, how many random sets should be chosen.

...

other arguments to pass to the stats::kmeans() function.

Value

If clusters_only is TRUE a vector of the new partition of the data is returned, i.e a vector of integers (from 1:k) indicating the cluster to which each observation is allocated.

Otherwise a list is returned with the following components:

clust_method

the name of the clustering method, i.e. "kmeans".

clusters

the vector of the new partition of the data, i.e. a vector of integers (from 1:k) indicating the cluster to which each observation is allocated.

...

an object of class "kmeans"

.

Author(s)

Aurore Archimbaud

See Also

stats::kmeans()

Examples

kmeans_clust(iris[,1:4], k = 3, clusters_only = TRUE)