Database Classification by Hybrid Method combining Supervised and Unsupervised Learnings

Torres-Moreno Juan-Manuel 1 Laurent Bougrain 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : 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.
Mots-clés : geographic information system minimerror hybrid method classification unsupervised learning méthode hybride apprentissage non supervisée système d'information géographique
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Communication dans un congrès
International Conference on Artificial Neural Networks - ICANN'2003, Jun 2003, Istambul, Turkey, pp.37-40, 2003
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Torres-Moreno Juan-Manuel, 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, 2003. 〈inria-00107724〉

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