[PDF.27ax] Learning from Data: Concepts, Theory, and Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

Learning from Data: Concepts, Theory, and Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

[PDF.yc03] Learning from Data: Concepts, Theory, and Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

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 | #3450897 in Books |  1998-03-25 | Ingredients: Example Ingredients | Original language:English | PDF # 1 |  9.55 x1.06 x6.24l,1.83 | File type: PDF | 464 pages

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||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 mac| |"This book contains considerable information on the concept of statistical learning theory.... However, some may find its presentation difficult to follow..." (Technometrics, February, 2001)

"...well readable..." (Zentralblatt Math, Vol.960, No.10

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, engineer...

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