RAUCH , G.

A validation procedure to evaluate the optimal number of clusters in a toxic activity data set using automatic classification by crisp partitioning clustering is here presented. The clustering procedures used are based on either the Kohonen, SOM, and kmeans joined algorithms. The clustering validation method consists in the use of an index...

A toxic activity data set has been processed by crisp partition-ing clustering. A validation procedure to evaluate the number of clusters is presented. The procedures is based on the use of SOM and k–means algorithms. The resulting clustering meth-od is based on the Mutual Information index, whose task is to identify the optimal number of...