Adaptive Learning of Polynomial Networks Genetic Programming, Backpropagation and Bayesian Methods
Heftet /
2011
/ Engelsk
Product details
ISBN
9781441940605
Published
2011-02-11
Publisher
Springer-Verlag New York Inc.
Height
235 mm
Width
155 mm
Age
Research, P, 06
Language
Product language
Engelsk
Format
Product format
Heftet
Number of pages
14
From the reviews: "This book describes induction of polynomial neural networks from data. ... This book may be used as a textbook for an advanced course on special topics of machine learning." (Jerzy W. Grzymala-Busse, Zentralblatt MATH, Vol. 1119 (21), 2007)
The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution.
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Offers a shift in focus from the standard linear models toward highly nonlinear models that can be inferred by contemporary learning approaches Presents alternative probabilistic search algorithms that discover the model architecture and neural network training techniques to find accurate polynomial weights Facilitates the discovery of polynomial models for time-series prediction Includes supplementary material: sn.pub/extras
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Product details
ISBN
9781441940605
Published
2011-02-11
Publisher
Springer-Verlag New York Inc.
Height
235 mm
Width
155 mm
Age
Research, P, 06
Language
Product language
Engelsk
Format
Product format
Heftet
Number of pages
14