A Bayesian analysis of self-organizing maps
Neural Computation
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This paper introduces a topological map dedicated to an automatic classification categorical data. Usually, topological maps uses a numerical (or binary) coding of the categorical data during the learning process. In the present paper, we propose a probabilistic formalism where the neurons now represent probability tables. Two examples using actual and synthetic data allow to validate the approach. The results show the good quality of the topological order obtained as well as its performances in classification.