Minimum Error Entropy Classification

Download or read book Minimum Error Entropy Classification written by Joaquim P. Marques de Sá and published by Springer. This book was released on 2012-07-25 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.