Library of American University of Madaba
Your cart is empty.
Marques de Sá, Joaquim P.
Minimum Error Entropy Classification [electronic resource] / by Joaquim P. Marques de Sá, Luís M.A. Silva, Jorge M.F. Santos, Luís A. Alexandre. - XVIII, 262 p. 110 illus. online resource. - Studies in Computational Intelligence, 420 1860-949X ; .
Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications.
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
9783642290299
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Statistical Physics, Dynamical Systems and Complexity.
006.3
Minimum Error Entropy Classification [electronic resource] / by Joaquim P. Marques de Sá, Luís M.A. Silva, Jorge M.F. Santos, Luís A. Alexandre. - XVIII, 262 p. 110 illus. online resource. - Studies in Computational Intelligence, 420 1860-949X ; .
Introduction -- Continuous Risk Functionals -- MEE with Continuous Errors -- MEE with Discrete Errors -- EE-Inspired Risks -- Applications.
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
9783642290299
Engineering.
Artificial intelligence.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Statistical Physics, Dynamical Systems and Complexity.
006.3