[Read free] Learning from Data: Concepts, Theory, and Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)
▲ Vladimir Cherkassky, Filip M. Mulier ▲
| #1552209 in Books | 1998-03-25 | Original language:English | PDF # 1 | 9.55 x1.06 x6.24l,1.83 | File Name: 0471154938 | 464 pages
||13 of 13 people found the following review helpful.| An up to date, unifying textbook on learning/modelling depen|By Oliver Femminella|The material contained in the textbook presents and discusses recent developments, but also important statistical (learning theory) concepts such as model selection, regularisation etc, in a unifying manner. Although the authors are somewhat biased towards kernel methods, support vector ma||"This book contains considerable information on the concept of statistical learning theory.... However, some may find its presentation difficult to follow..." (Technometrics, February, 2001)
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, enginee...
[PDF.zu47] Learning from Data: Concepts, Theory, and Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control) Rating: 3.75 (521 Votes)
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