En este trabajo se describe la red neuronal como modelo estadístico no lineal, y se presenta aplicaciones de los métodos de combinación de clasificadores ‘’bagging’’ y ‘’boosting’’ en redes neuronales a las bases de datos sonar e iris, como una alternativa de reducción de la tasa de mala clasificación del método de redes neuronales. / In this thesis is described a neural networks as statistic model non linear and it study the method of the combination of classifiers bagging and boosting in neural networks as an alternative of reduction of the wrong rate’s classifiers for the method of neural networks. As application of this procedures are analyzed the base of dates. They are very known as ‘’ sonar’’ and ‘’iris’’.
| Identifer | oai:union.ndltd.org:Cybertesis/sdx:www.cybertesis.edu.pe:80:sisbib/documents/sisbib.2007.torre_dc-principal |
| Date | January 2007 |
| Creators | Torre Dueñas, Cleto de la |
| Publisher | Universidad Nacional Mayor de San Marcos. Programa Cybertesis PERÚ |
| Source Sets | Universidad Nacional Mayor de San Marcos - SISBIB PERU |
| Language | Spanish |
| Detected Language | English |
| Format | text/xml |
| Rights | Torre Dueñas, Cleto de la, cleto_de_la_torre@hotmail.com |
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