SimilarityMeasure: A measure of similarity for the outputs of the different...

In IntClust: Integrated Data Analysis via Clustering

Description

The function SimilarityMeasure computes the similarity of the methods. Given a list of outputs as input, the first element will be seen as the reference. Function MatrixFunction is called upon and the cluster numbers are rearranged according to the reference. Per method, SimilarityMeasure investigates which objects have the same cluster number in reference and said method. This number is divided by the total number of objects and used as a similarity measure.

Usage

SimilarityMeasure(List, nrclusters = NULL, fusionsLog = TRUE, 
WeightClust = TRUE, names = NULL)

Arguments

List	A list of clustering outputs to be compared. The first element of the list will be used as the reference in ReorderToReference.
nrclusters	The number of clusters to cut the dendrogram in.~~
fusionsLog	To be handed to MatrixFunction.
WeightClust	To be handed to MatrixFunction.
names	Optional. Names of the methods.

Value

A vector of similarity measures, one for each method given as input.

Author(s)

Marijke Van Moerbeke

Examples

data(fingerprintMat)
data(targetMat)

MCF7_F = Cluster(fingerprintMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="ward",gap=FALSE,maxK=55,StopRange=FALSE)
MCF7_T = Cluster(targetMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="ward",gap=FALSE,maxK=55,StopRange=FALSE)

L=list(MCF7_F,MCF7_T)
names=c("FP","TP")

MCF7_SimFandT=SimilarityMeasure(L,nrclusters=7,fusionsLog=TRUE,WeightClust=TRUE,
names=names)

IntClust documentation built on May 2, 2019, 5:23 p.m.