Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Paperback, Softcover reprint of hardcover 1st ed. 2008)


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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Product Description

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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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Series

Studies in Computational Intelligence, 98

Release date

November 2010

Availability

Expected to ship within 10 - 15 working days

First published

2008

Editors

, ,

Dimensions

235 x 155 x 9mm (L x W x T)

Format

Paperback

Pages

162

Edition

Softcover reprint of hardcover 1st ed. 2008

ISBN-13

978-3-642-09615-0

Barcode

9783642096150

Categories

LSN

3-642-09615-8



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