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Innovations in Machine Learning: Theory and Applications

Innovations in Machine Learning: Theory and Applications

David Heckerman, Christopher Meek, Gregory Cooper (auth.), Professor Dawn E. Holmes, Professor Lakhmi C. Jain (eds.)
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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.

年:
2006
出版:
1
出版社:
Springer-Verlag Berlin Heidelberg
语言:
english
页:
276
ISBN 10:
3540334866
ISBN 13:
9783540334866
系列:
Studies in Fuzziness and Soft Computing 194
文件:
PDF, 2.55 MB
IPFS:
CID , CID Blake2b
english, 2006
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Pravin Lal

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