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....
"I think Learning From Data is a very valuable volume. I will recommend it to my graduate students." ( Journal of the American Statistical Association, March 2009)
"The broad spectrum of information it offers is beneficial to many field of research. The selection of topics is good, and I believe that many researchers and practioners will find this book useful." (Technometrics, May 2008)
"The authors have succeeded in summarizing...
An interdisciplinary framework for learning methodologies now revised and updated
Learning from Data 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 pattern recognition can be applied showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer...
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