Learning Classifier Systems in Data Mining

Larry Bull

ISBN 10: 3642097758 / ISBN 13: 9783642097751

Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783642097751

Bibliographic Details

• Title: Learning Classifier Systems in Data Mining
• Publisher: Springer Berlin Heidelberg, Springer Berlin Heidelberg
• Publication Date: 2010
• Language: English
• ISBN 10: 3642097758
• ISBN 13: 9783642097751
• Binding: Taschenbuch
• Condition: Neu

About this title

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.