Evacluster (version 0.1.0)

hierarchicalCluster: 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

# NOT RUN {
library(datasets)
data(iris)

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

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