Learning Classifier Systems in Data Mining
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Beschreibung
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.
Brings together recent data mining applications of a machine learning technique Covers a wide range of domains demonstrating the utility of the Learning Classifier Systems technique Includes supplementary material: sn.pub/extras
Autor*in
Larry Bull
Themen in »Learning Classifier Systems in Data Mining«
classification clustering cognition data mining evolution evolutionary computation fuzzy logic knowledge knowledge discovery learning machine learning modeling proving robotics supervised learning