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Database Classification by Hybrid Method combining Supervised and Unsupervised Learnings

Juan-Manuel Torres-Moreno 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.
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Submitted on : Thursday, October 19, 2006 - 9:07:02 AM
Last modification on : Friday, February 4, 2022 - 3:15:45 AM
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  • HAL Id : inria-00107724, version 1



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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