Jaume Bacardit; Ester Bernadó-Mansilla; Martin V. Butz; Tim Kovacs; Xavier Llorà; Keiki Takadama Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2008) Pehmeäkantinen kirja
Jaume Bacardit; Will Browne; Jan Drugowitsch; Ester Bernadó-Mansilla; Martin V. Butz Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2011) Pehmeäkantinen kirja
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.
