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Detalles bibliogr�ficos

T�tulo: Optimal Bayesian Classification (Press Monograph)
Editor: SPIE Press
Fecha de publicaci�n: 2020
Idioma: Ingl�s
ISBN 10: 1510630694
ISBN 13: 9781510630697
Encuadernaci�n: paperback
Estado: Very Good

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Sinopsis

The most basic problem of engineering is the design of optimal operators. Design takes different forms depending on the random process constituting the scientific model and the operator class of interest. For classification, the random process is a feature-label distribution, and a Bayes classifier minimizes classification error. Rarely do we know the feature-label distribution or have sufficient data to estimate it.

To best use available knowledge and data, this book takes a Bayesian approach to modeling the feature-label distribution and designs an optimal classifier relative to a posterior distribution governing an uncertainty class of feature-label distributions. The origins of this approach lie in estimating classifier error when there are insufficient data to hold out test data, in which case an optimal error estimate can be obtained relative to the uncertainty class. A natural next step is to forgo classical ad hoc classifier design and find an optimal classifier relative to the posterior distribution over the uncertainty class - this being an optimal Bayesian classifier.

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Charlotte y Peter Fiell son dos autoridades en historia, teor�a y cr�tica del dise�o y han escrito m�s de sesenta libros sobre la materia, muchos de los cuales se han convertido en �xitos de ventas. Tambi�n han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Dise�o del siglo XX, El dise�o industrial de la A a la Z, Scandinavian Design y Dise�o del siglo XXI.

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