Learning from Data: Concepts, Theory, and Methods, 2nd Edition eBook

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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.

This is a digital product.

Learning from Data: Concepts, Theory, and Methods 2nd Edition is written by Vladimir Cherkassky; Filip M. Mulier and published by Wiley-IEEE Press. The Digital and eTextbook ISBNs for Learning from Data are 9780470140512, 0470140518 and the print ISBNs are 9780471681823, 0471681822. Additional ISBNs for this eTextbook include 9780470140529.