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Item Details
Title:
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LEARNING CLASSIFIER SYSTEMS IN DATA MINING
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By: |
Larry Bull (Editor), Ester Bernado-Mansilla (Editor), John Holmes (Editor) |
Format: |
Hardback |
List price:
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£149.99 |
We currently do not stock this item, please contact the publisher directly for
further information.
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ISBN 10: |
3540789782 |
ISBN 13: |
9783540789789 |
Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
Pub. date: |
1 May, 2008 |
Edition: |
2008 ed. |
Series: |
Studies in Computational Intelligence 125 |
Pages: |
230 |
Description: |
The ability of Learning Classifier Systems (LCS) to solve complex real-world problems is becoming clear. This book brings together work by a number of individuals who demonstrate the good performance of LCS in a variety of domains. |
Synopsis: |
Just over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear. In particular, their capability for rule induction in data mining has sparked renewed interest in LCS. This book brings together work by a number of individuals who are demonstrating their good performance in a variety of domains. The first contribution is arranged as follows: Firstly, the main forms of LCS are described in some detail. A number of historical uses of LCS in data mining are then reviewed before an overview of the rest of the volume is presented. The rest of this book describes recent research on the use of LCS in the main areas of machine learning data mining: classification, clustering, time-series and numerical prediction, feature selection, ensembles, and knowledge discovery. |
Illustrations: |
53 Tables, black and white; IX, 230 p. |
Publication: |
Germany |
Imprint: |
Springer-Verlag Berlin and Heidelberg GmbH & Co. K |
Returns: |
Returnable |
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Ramadan and Eid al-Fitr
A celebratory, inclusive and educational exploration of Ramadan and Eid al-Fitr for both children that celebrate and children who want to understand and appreciate their peers who do.
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