IntClust (version 0.1.0)

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

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. Default is NULL.

fusionsLog

Logical. To be handed to ReorderToReference: indicator for the fusion of clusters. Default is TRUE

weightclust

Logical. To be handed to ReorderToReference: to be used for the outputs of CEC, WeightedClust or WeightedSimClust. If TRUE, only the result of the Clust element is considered. Default is TRUE.

names

Optional. Names of the methods.

Value

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

Examples

# NOT RUN {
data(fingerprintMat)
data(targetMat)

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

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

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


# }