Studies in Fuzziness and Soft Computing

Theory and Applications

By: Dawn E. Holmes (Editor)

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Hardcover | 9 March 2006

At a Glance

Hardcover
296 Pages

Dimensions(cm)
23.5 x 15.88 x 1.27

Hardcover

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Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained.

Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Mathematics Applied Mathematics Artificial Intelligence Machine Learning Engineering & Technology Technology in General Maths for Engineers Engineering in General

A Bayesian approach to causal discovery	p. 1
A tutorial on learning causal influence	p. 29
Learning based programming	p. 73
N-1 experiments suffice to determine the causal relations among N variables	p. 97
Support vector inductive logic programming	p. 113
Neural probabilistic language models	p. 137
Computational grammatical inference	p. 187
On kernel target alignment	p. 205
The structure of version space	p. 257
Table of Contents provided by Blackwell. All Rights Reserved.

Studies in Fuzziness and Soft Computing

Theory and Applications

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

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