Model collisions in the dissimilarity SOM

We investigate in this paper the problem of model collisions in the Dissimilarity Self Organizing Map (SOM). This extension of the SOM to dissimilarity data suffers from constraints imposed on the model representation, that lead to some strong map folding: several units share a common prototype. We propose in this paper an efficient way to address this problem via a branch and bound approach.

• Type: Conference
• Year: 2007
• Where: ESANN
• Authors: Fabrice Rossi
• Keywords: Dissimilarity Data Suffers, ESANN 2007, Model Collisions, Neural Networks, Self Organizing Map