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Constrained domain maximum likelihood estimation and the loss function in statistical pattern recognition

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Constrained domain maximum likelihood estimation and the loss function in statistical pattern recognition

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Andrés Ferrer, J. (2008). Constrained domain maximum likelihood estimation and the loss function in statistical pattern recognition. http://hdl.handle.net/10251/13638.

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Title: Constrained domain maximum likelihood estimation and the loss function in statistical pattern recognition
Author:
Director(s): Juan Císcar, Alfonso
UPV Unit: Universitat Politècnica de València. Servicio de Alumnado - Servei d'Alumnat
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2008-11
Issued date:
Abstract:
In this thesis we present a new estimation algorithm for statistical models which does not incurs in the over-trainning problems. This new estimation techinque, the so-called, constrained domain maximum likelihood estimation ...[+]
Subjects: Maximum likelihood , Maximum constrained likelihood , Loss function , Karush kunh tucker conditions , Minimun risk , Statistical machine translation , Naive bayes
Copyrigths: Reserva de todos los derechos
degree: Máster Universitario en Inteligencia Artificial, Reconocimiento de Formas e Imagen Digital-Màster Universitari en Intel·Ligència Artificial, Reconeixement de Formes i Imatge Digital
Type: Tesis de máster

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