CompareInteractive: Interactive comparison of clustering results for a specific...

Description Usage Arguments Value Examples

Description

A visual comparison of all methods is handy to see which objects will always cluster together independent of the applied methods. The function CompareInteractive plots the comparison over the specified methods. A cluster or method can than be identified by clicking and is plotted separately against the single source or other specified methods.

Usage

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CompareInteractive(ListM, ListS, nrclusters = NULL, cols = NULL,
  fusionsLogM = FALSE, fusionsLogS = FALSE, weightclustM = FALSE,
  weightclustS = FALSE, namesM = NULL, namesS = NULL, marginsM = c(2,
  2.5, 2, 2.5), marginsS = c(8, 2.5, 2, 2.5), Interactive = TRUE, n = 1)

Arguments

ListM

A list of the multiple source clustering or other methods to be compared and from which a cluster or method will be identified. The first element of the list will be used as the reference in ReorderToReference.

ListS

A list of the single source clustering or other methods the identified result will be compared to. 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.

cols

A character vector with the names of the colours. Default is NULL.

fusionsLogM

The fusionsLog parameter for the elements in ListM. To be handed to ReorderToReference. Default is FALSE.

fusionsLogS

The fusionslog parameter for the elements in ListS. To be handed to ReorderToReference. Default is FALSE.

weightclustM

The weightclust parameter for the elements in ListM. To be handed to ReorderToReference. Default is FALSE.

weightclustS

The weightclust parameter for the elements in ListS. To be handed to ReorderToReference. Default is FALSE.

namesM

Optional. Names of the multiple source clusterings to be used as labels for the columns. Default is NULL.

namesS

Optional. Names of the single source clusterings to be used as labels for the columns. Default is NULL.

marginsM

Optional. Margins to be used for the plot for the elements is ListM after the identification. Default is c(2,2.5,2,2.5).

marginsS

Optional. Margins to be used for the plot for the elements is ListS after the identification. Default is c(8,2.5,2,2.5).

Interactive

Optional. Do you want an interactive plot? Defaults to TRUE, if not the function provides the same as ComparePlot for the elements in ListM. Default is TRUE.

n

The number of methods/clusters you want to identify. Default is 1.

Value

The returned value is a plot of the comparison of the elements of ListM. On this plot multiple clusters and/or methods can be identified. Click on a cluster of a specific method to see how that cluster of that method compares to the elements in ListS. Click left next to a row to identify a all cluster of a specific method. A new plotting window will appear for every identification.

Examples

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## Not run: 
data(fingerprintMat)
data(targetMat)
data(Colors1)

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(fingerprintMat,targetMat)

MCF7_W=WeightedClust(List=L,type="data",distmeasure=c("tanimoto","tanimoto"),
normalize=c(FALSE,FALSE),method=c(NULL,NULL),weight=seq(1,0,-0.1),weightclust=0.5,
clust="agnes",linkage="ward",StopRange=FALSE)

ListM=list(MCF7_W)
namesM=c(seq(1.0,0.0,-0.1))

ListS=list(MCF7_F,MCF7_T)
namesS=c("FP","TP")

CompareInteractive(ListM,ListS,nrclusters=7,cols=Colors1,fusionsLogM=FALSE,
fusionsLogS=FALSE,weightclustM=FALSE,weightclustS=TRUE,namesM,namesS,
marginsM=c(2,2.5,2,2.5),marginsS=c(8,2.5,2,2.5),Interactive=TRUE,n=1)

## End(Not run)

IntClust documentation built on May 2, 2019, 5:51 a.m.