kml (version 0.9.2)

Clusterization-class: ~ Class: Clusterization ~

Description

An object of class Clusterization is a partition of trajectories in subgroups. The object also contains some information like the percentage of trajectories that each group contains or the Calinski criterion.

Objects from the Class

Objects are not intend to be created by users. Clusterization are created by kml and directly added to a "ClusterizLongData" object.

validation rules

A class Clusterization object must follow some rules to be valid:

• The slot should be either all empty, or all non empty.
• nbClustershas to be lower or equal to 25 (twenty five clusters maximum).
• clustersandidhave to have the same length.
• clustershas to be a factor inLETTERS[1:nbCluster](withnbClusterslower than 25).
• table(clusters)has to be in the reverse order (clusters are sorted form the biggest to the smallest).
• idcannot be duplicated.
• anidcannot be missing.

Construction

Class Clusterization objects are constructed through the kml procedure and are directy add to a ClusterizLongData object. They are not intend to be construct by the users.

Author(s)

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

English translation

Rapha�l Ricaud Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory University of Paris 10 / Nanterre

References

Article submited Web site: http://christophe.genolini.free.fr/kml

See Also

Overview: kml-package Classes : ClusterizLongData, Clusterization, ArtificialLongData Methods : kml

Examples

showClass("Clusterization")