The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.
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The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.
Imprint | Springer-Verlag |
Country of origin | Germany |
Series | Studies in Computational Intelligence, 98 |
Release date | March 2008 |
Availability | Expected to ship within 10 - 15 working days |
First published | May 2008 |
Editors | Ashish Ghosh, Satchidananda Dehuri, Susmita Ghosh |
Dimensions | 235 x 155 x 11mm (L x W x T) |
Format | Hardcover |
Pages | 162 |
Edition | 2008 ed. |
ISBN-13 | 978-3-540-77466-2 |
Barcode | 9783540774662 |
Categories | |
LSN | 3-540-77466-1 |