sbp_kmeans: The successive binary partition k-means algorithm.

In akinori-ito/successive-binary-partition-kmeans: Successive binary partition k-means algorithm

The successive binary partition k-means algorithm.

Description

The successive binary partition k-means algorithm.

Usage

sbp_kmeans(x, n, iter.final = 0, iter.max = 20, algorithm = "Hartigan-Wong")

Arguments

x	A matrix or data frame. Each row corresponds to the each data.
n	Number of clusters.
iter.final	Number of iteration at the final centroid refinement.
iter.max	Number of maximum iteration in each split.
algorithm	Gigen to kmeans().

Value

List of the clustering result. cluster: a vector indicating the cluster numbers of the samples. centers: a matrix of the centroids size: a vector of the cluster sizes

akinori-ito/successive-binary-partition-kmeans documentation built on Nov. 26, 2024, 2:48 a.m.