Dynamical Clustering of Interval Data: Optimization of an Adequacy Criterion Based on Hausdorff Distance

In order to extend the dynamical clustering algorithm to interval data sets, we define the prototype of a cluster by optimization of a classical adequacy criterion based on Hausdorff distance. Once this class prototype properly defined we give a simple and converging algorithm for this new type of interval data.