25.6.11

Learning from Data: Concepts, Theory, and Methods


Vladimir Cherkassky, Filip M. Mulier, "Learning from Data:
Concepts, Theory, and Methods"
Wiley-IEEE Press; 2 edition |(2007-08-24| ISBN:0471681822 | 538 pages | PDF | 3,5 MB

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.

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