Learning from Data: Concepts, Theory, and Methods (Wiley - IEEE)

Vladimir Cherkassky, Filip M. Mulier

ISBN 10: 0471681822 / ISBN 13: 9780471681823

Editore: Wiley-Blackwell 2007-09-11, 2007

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Codice articolo 6666-WLY-9780471681823

Dati bibliografici

Titolo: Learning from Data: Concepts, Theory, and ...

Casa editrice: Wiley-Blackwell 2007-09-11

Data di pubblicazione: 2007

Legatura: Hardcover

Condizione: New

Edizione: seconda edizione

Descrizione articolo

Riassunto:

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.

Informazioni sull?autore:

Vladimir CherKassky, PhD, is Professor of Electrical and Computer Engineering at the University of Minnesota. He is internationally known for his research on neural networks and statistical learning.

Filip Mulier, PhD, has worked in the software field for the last twelve years, part of which has been spent researching, developing, and applying advanced statistical and machine learning methods. He currently holds a project management position.