Combining Supervised and Unsupervised Learning for GIS Classification

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This paper presents a new hybrid learning algorithm for unsupervised classification tasks. We combined Fuzzy c-means learning algorithm and a 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 features of a Geographic Information System (GIS), allows to well classify it. Finally, we compared our results to a classical supervised classification obtained by a multilayer perceptron.
8 pages, 3 figures

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Machine Learning

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http://salesiana.dossiersoluciones.com/handle/123456789/230365

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0905.2347
 http://arxiv.org/abs/0905.2347

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arXiv