Description: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Ashish Ghosh, Satchidananda Dehuri, Susmita Ghosh Format: Paperback Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Germany Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K ISBN-13: 9783642096150, 978-3642096150 Synopsis 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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Book Title: Multi-Objective Evolutionary Algorithms for Knowledge Discover...
Number of Pages: 162 Pages
Language: English
Publication Name: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
Publisher: Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG
Publication Year: 2010
Subject: Engineering & Technology, Computer Science
Item Height: 235 mm
Item Weight: 278 g
Type: Textbook
Author: Ashish Ghosh, Satchidananda Dehuri, Susmita Ghosh
Series: Studies in Computational Intelligence
Item Width: 155 mm
Format: Paperback
