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Learning Classifier Systems in Data Mining (Paperback, Softcover reprint of hardcover 1st ed. 2008) Loot Price: R4,338
Discovery Miles 43 380
Learning Classifier Systems in Data Mining (Paperback, Softcover reprint of hardcover 1st ed. 2008): Larry Bull, Ester...

Learning Classifier Systems in Data Mining (Paperback, Softcover reprint of hardcover 1st ed. 2008)

Larry Bull, Ester Bernado-Mansilla, John Holmes

Series: Studies in Computational Intelligence, 125

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Loot Price R4,338 Discovery Miles 43 380 | Repayment Terms: R407 pm x 12*

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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.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Studies in Computational Intelligence, 125
Release date: November 2010
First published: 2008
Editors: Larry Bull • Ester Bernado-Mansilla • John Holmes
Dimensions: 235 x 155 x 12mm (L x W x T)
Format: Paperback
Pages: 230
Edition: Softcover reprint of hardcover 1st ed. 2008
ISBN-13: 978-3-642-09775-1
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-642-09775-8
Barcode: 9783642097751

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