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Learning from Data
Concepts, Theory, and Methods
E-Book
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9780470140512
Veröffentl:
2008
Einband:
E-Book
Seiten:
560
Autor:
Vladimir Cherkassky
Serie:
1, Wiley - IEEE
eBook Typ:
PDF
eBook Format:
Reflowable E-Book
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:
An interdisciplinary framework for learning methodologies covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
An interdisciplinary framework for learning methodologies--covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.