hierarchicalCluster: hierarchical clustering

In FahimehN/Evacluster-Package: Evaluation Clustering Methods for Disease Subtypes Diagnosis

hierarchical clustering

Description

This function seeks to build a hierarchy of clusters

Usage

hierarchicalCluster(data = NULL, distmethod = NULL, clusters = NULL, ...)

Arguments

data	A Data set
distmethod	The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski".
clusters	The number of Clusters
...	Additional parameters passed to hclust function

Value

A list of cluster labels

Examples

library(datasets)
data(iris)

rndSamples <- sample(nrow(iris),100)
trainData <- iris[rndSamples,]
testData <- iris[-rndSamples,]

cls <- hierarchicalCluster(trainData[,1:4],distmethod="euclidean",clusters=3)

FahimehN/Evacluster-Package documentation built on April 4, 2022, 10:37 a.m.