| 书目名称 | Minimum Error Entropy Classification | | 编辑 | Joaquim P. Marques de Sá,Luís M.A. Silva,Luís A. A | | 视频video | | | 概述 | Presents data classification methodologies based on a minimum error entropy approach.Includes both theoretical results and applications to real world datasets.Written by leading experts in the field | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Book 2013 | | 关键词 | Computational Intelligence; Information Theoretic Learning; Minimum Error Entropy Classification | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-29029-9 | | isbn_softcover | 978-3-642-43742-7 | | isbn_ebook | 978-3-642-29029-9Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | Springer-Verlag Berlin Heidelberg 2013 |
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发表于 2025-3-21 17:30:46
