Clusterization

Clusterization-class

[,Clusterization-method

[,Clusterization

An object of class <code>Clusterization</code> is a <code><a href="/link/Partition?package=kml&version=2.1.2&to=longitudinalData%3APartition-class" rd-options="longitudinalData:Partition-class" data-mini-rdoc="longitudinalData:Partition-class::Partition">Partition</a></code> of
  trajectories in subgroups. The object also contains some information like the
  percentage of trajectories that each group contains or a quality criterion.

classes

cluster

classif

nonparametric

KmL is an implementation of k-means specifically design to
        cluster longitudinal data. It provides facilities to deal with
        missing value, compute several quality criterion (Calinski and
        Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and
        propose a graphical interface for choosing the 'best' number of
        clusters.

Christophe Genolini

K-means for Longitudinal data

Clusterization-class function

Objects are not intend to be created by users. <code>Clusterization</code> are created
  by <code>kml</code> and directly added to a <code><links4class>ClusterizLongData</links4class></code> object.

Objects from the Class

An object <code>Clusterization</code> must follow the same rules than a
  <code><a href="/link/Partition?package=kml&version=2.1.2&to=longitudinalData%3APartition-class" rd-options="longitudinalData:Partition-class" data-mini-rdoc="longitudinalData:Partition-class::Partition">Partition</a></code>.

validation rules

Class <code>Clusterization</code> objects are constructed through the
  <code><a href="/link/kml?package=kml&version=2.1.2" rd-options="" data-mini-rdoc="kml::kml">kml</a></code> procedure and are directy add to a
  <code>ClusterizLongData</code> object. They can also be construct
  by the users using <code><a href="/link/clusterization?package=kml&version=2.1.2" rd-options="" data-mini-rdoc="kml::clusterization">clusterization</a></code>.

Construction

<code>Clusterization</code> are not intend to be modified, no setteur is define.

Setteur

Christophe GenoliniPSIGIAM: Paris Sud Innovation Group in Adolescent Mental HealthINSERM U669 / Maison de Solenn / ParisContact author : <genolini@u-paris10.fr></genolini@u-paris10.fr>

Author(s)

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

Clusterization-class: ~ Class: Clusterization ~

Description

Arguments

Objects from the Class

validation rules

Construction

Setteur

Author(s)

English translation

References

See Also

Examples