| Title:
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INNOVATIONS IN MACHINE LEARNING
THEORY AND APPLICATIONS |
| By: |
Dawn E. Holmes (Editor) |
| Format: |
Hardback |
| List price:
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£149.99 |
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| ISBN 10: |
3540306099 |
| ISBN 13: |
9783540306092 |
| Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
| Pub. date: |
9 March, 2006 |
| Edition: |
2006 ed. |
| Series: |
Studies in Fuzziness and Soft Computing 194 |
| Pages: |
276 |
| Description: |
Covers the three main machine learning systems - symbolic learning, neural networks and genetic algorithms. This work also provides a tutorial on learning casual influences and is useful to theoreticians and application scientists/engineers in the broad area of artificial intelligence. |
| Synopsis: |
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. |
| Illustrations: |
28 Tables, black and white; XVI, 276 p. |
| Publication: |
Germany |
| Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
| Returns: |
Returnable |