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Communication Dans Un Congrès Année : 2003

Database Classification by Hybrid Method combining Supervised and Unsupervised Learnings

Juan-Manuel Torres-Moreno
Laurent Bougrain
Frédéric Alexandre

Résumé

This paper presents a new hybrid learning algorithm for unsupervised classification tasks. We combined Fuzzy c-means learning and the supervised version of Minimerror to develop a hybrid incremental strategy allowing unsupervised classifications. We applied this new approach to a real-world database in order to know if the information contained in unlabeled signals of a Geographic Information System (GIS), allow to well classify it. Finally, we compared our results to a classical classification obtained by a multilayer perceptron.
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Dates et versions

inria-00107724 , version 1 (19-10-2006)

Identifiants

  • HAL Id : inria-00107724 , version 1

Citer

Juan-Manuel Torres-Moreno, Laurent Bougrain, Frédéric Alexandre. Database Classification by Hybrid Method combining Supervised and Unsupervised Learnings. International Conference on Artificial Neural Networks - ICANN'2003, Jun 2003, Istambul, Turkey, pp.37-40. ⟨inria-00107724⟩
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