choice {kml}R Documentation

~ function: choice ~

Description

choice lets the user choose the Clusterization he wants to export.

Usage

choice(x)

Arguments

x [ClusterizLongData]: Contains all the clusterization found by KmL.

Details

choice run in three steps:

  1. Choice of the Clusterization
  2. Exporting the Clusterization
  3. Selection of a graphic representation.

Value

Non applicable

1. Choice of the this-is-escaped-codenormal-bracket19bracket-normal

choice opens two graphic windows. In the left one, the Calinski criteria of all Clusterization found by kml are represented. They are filed according to the number of clusters, from the biggest to the smallest. This windows let the user to select a Clusterization. The selected Clusterization is pointed with a dark spot.

In the right window, the Clusterization selected by the user is represented.

When choice is called, the Clusterization having the larger Calinski criterion is selected. It is possible to visualize the other Clusterization by using the arrows on the keyboard.

When the choice of a Clusterization has been made and needs to be exported, the use can go on to the next step by pressing "Return".

2. Exporting the this-is-escaped-codenormal-bracket32bracket-normal

When a Clusterization is being chosen, there are three possibilities :

  1. "Return" enables the visualization Clusterization on screen (but nothing else).
  2. Entering the name of a file nomDeFichier enables the user to export the Clusterization. Clusters are exported in the file nomDeFichier-cluster.csv. Criteria are exported in nomDeFichier-criteres.csv. Distances and posterior probabilities are in nomDeFichier-distance.csv (not implemented yet).
  3. Entering a name preceded by the symbol -> (like ->variablesNames) enables the user to save the Clusterization. Clusters are stored in the variable nomVariable_cluster.csv as a data.frame. Criteria are saved in nomDeVariable_criters.csv as lists. Distances and posterior probabilities are saved nomDeVariable_distance.csv (not implemented yet).

3. Selection of a graphic representation

Finally, it is possible to export a graphic representation of the Clusterization. With the keyboard, the user can modify the aspect of the graph.

More precisely:

When the final graph is choisen by pressing "Return". It can then be exported as usual with a right click on the figure.

Author(s)

Christophe Genolini
PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health
INSERM U669 / Maison de Solenn / Paris

Responsable : <genolini@u-paris10.fr>

English translation

Raphaël Ricaud
Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory
University of Paris 10 / Nanterre

See Also

kml-package

Examples

cld1 <- as.cld(gald())
kml(cld1,2:3,3)
#choice(cld1)

[Package kml version 0.9.0 Index]