scheme_sub_km: Subsampling-based K-means Clustering

In bootcluster: Bootstrapping Estimates of Clustering Stability

Subsampling-based K-means Clustering

Description

Subsampling-based K-means Clustering

Usage

scheme_sub_km(df, nk, B = 20, cut_ratio = 0.5, r = 5)

Arguments

df	data.frame or matrix of the dataset
nk	number of clusters
B	number of bootstrap samples
cut_ratio	ratio for subsampling (default: 0.5)
r	number of k-means runs (default: 5)

Value

List containing clustering results and stability measures

bootcluster documentation built on April 3, 2025, 7:45 p.m.