distlim_hclust_clustering: Categorize multi dimension data based on the relative...

In hmito/hmRLib: Helper library for numerical analysis with R

Categorize multi dimension data based on the relative distance vs cluster size using hclust function

Description

Based on the h-clustering algorithm, find optimal cluster num by keeping multiple cluster are not overlapped.

Usage

distlim_hclust_clustering(data, thr = 5, kmax = 10, method = "ward.D2")

Arguments

data	Matrix data for clustering. Row is element and Col is axis.
thr	Threshold value of the relative distance/size of clusters.
kmax	Max cluster number.
method	Clustering method in hclust.

Value

List with size: number of cluster and group: #cluster of each element.

hmito/hmRLib documentation built on March 13, 2024, 9:41 p.m.