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Book synopsis

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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Learning from Data - Concepts, Theory and Methods 2e
• Author: Vladimir Cherkassky, Filip M. Mulier
• Language: English
• Binding: Hardback
• Number of pages: 560
• EAN: 9780471681823
• ISBN: 0471681822
• ID: 04892976
• Publisher: John Wiley & Sons Inc
• Weight: 906 g
• Dimensions: 244 × 157 × 38 mm
• Date of publishing: 11. September 2007

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