rpuHclust {rpud}R Documentation

Hierarchical Clustering

Description

This function finds hierarchical clusters from a distance matrix based an agglomerative algorithms.

Usage

     rpuHclust(d, method="complete", members=NULL)

Arguments

d

a dissimilarity structure as produced by dist or rpuDist.

method

the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of "ward", "single", "complete", "average", "mcquitty", "median" or "centroid".

members

NULL or a vector with length size of d. See the ‘Details’ section.

Details

Perform hierarchical clusterings with the rpudplus add-on for rpud. In absense of rpudplus, rpud perform the cluster analysis with the default R implementation, and there will be no speed gain.

Value

An object of class hclust which describes the tree produced by the clustering process.

See Also

hclust, gpuHclust

Examples

## Not run: 
    numVectors <- 5
    dimension <- 10
    Vectors <- matrix(runif(numVectors*dimension), numVectors, dimension)
    distMat <- rpuDist(Vectors, "euclidean")
    myClust <- rpuHclust(distMat, "single")
    plot(myClust)

## End(Not run)

[Package rpud version 0.7.0 Index]