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longitudinalData (version 2.4.7)

plotCriterion: ~ Function: plotCriterion ~

Description

This function graphically displays the quality criterion of all the Partition of a ListPartition object.

Usage

plotCriterion(x, criterion=x["criterionActif"],nbCriterion=100)

Value

No value are return. A graph is printed.

Arguments

x

[ClusterLongData]: object whose quality criterion should be displayed.

criterion

[character]: name of the criterion(s) to plot. It can either display all the value for a single specific criterion or display several criterion, only the best value for each clusters number and for each criterion.

nbCriterion

[numeric]: if there is a big number of Partition, the graphical display of all of them can be slow. nbCriterion lets the user limit the number of criteria that will be taken in account.

Details

This function display graphically the quality criterion (probably to decide the best clusters' number). It can either display all the criterion ; this is useful to see the consistency of the result : is the best clusterization obtain several time or only one ? It can also display only the best result for each clusters number : this helps to find the local maximum, which is classically used to chose the "correct" clusters' number.

Examples

Run this code
###############
### Data generation
data(artificialLongData)
traj <- as.matrix(artificialLongData[,-1])

### Some clustering
listPart <- listPartition()
listPart["add"] <- partition(rep(c("A","B"),time=100),traj)
listPart["add"] <- partition(rep(c("A","B","B","B"),time=50),traj)
listPart["add"] <- partition(rep(c("A","B","C","A"),time=50),traj)
listPart["add"] <- partition(rep(c("A","B","C","D"),time=50),traj)
ordered(listPart)

################
### graphical display
plotCriterion(listPart)
plotAllCriterion(listPart,criterion=CRITERION_NAMES[1:5],TRUE)

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