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.
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Ngôn ngữ Anh ● định dạng PDF ● ISBN 9783642290299 ● Nhà xuất bản Springer Berlin Heidelberg ● Được phát hành 2012 ● Có thể tải xuống 3 lần ● Tiền tệ EUR ● TÔI 6322794 ● Sao chép bảo vệ Adobe DRM
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