Participants : Marc Csernel, Sergiu Chelcea, Alzennyr da Silva, Francesco de Carvalho, Yves Lechevallier [ co-correspondant ] , Fabrice Rossi, Brigitte Trousse [ co-correspondant ] .
For clustering, we maintained a clustering toolbox, written in C++ and Java, that includes several clustering methods developed by the team over time, and uses the SOM library developed by M. Csernel. This library offers a common data interface to every algorithm. This toolbox supports developers in integrating various classification methods, and testing and comparing with other methods. Currently it integrates several methods:
from AxIS Rocquencourt: 1) a partitionning clustering method on complex data tables called SCluster  , 2) Div (in C++)  , 2) a java library that provides efficient implementations of several SOM variants, especially those that can handle dissimilarity data called DSOM  , which is available on Inria's Gforge server http://gforge.inria.fr/projects/somlib/ (cf. section 6.3.2 ) and 3) a functional Multi-Layer Perceptron Method called FNET for the classification of functional data  ;
two partitionning clustering methods on the dissimilarity tables issued from a collaboration between AxIS Rocquencourt team and Recife University, Brazil: 1) CDis (in C++)  and 2) CCClust (in C++);
2-3 AHC (in Java) from AxIS Sophia Antipolis which is available as a Java applet which runs the ``hierarchies visualisation'' toolbox.
We developed a Web interface for this clustering toolbox for the following methods: SCluster, Div, Cdis, CCClust. Such an interface is developed in C++ and runs on our Apache internal Web server.