Multiobjective Genetic Algorithms for Clustering Applications in Data Mining and Bioinformatics / by Ujjwal Maulik, Sanghamitra Bandyopadhyay, Anirban Mukhopadhyay.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft...

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Bibliographic Details
Main Authors: Maulik, Ujjwal (Author), Bandyopadhyay, Sanghamitra (Author), Mukhopadhyay, Anirban (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.
Edition:1st ed. 2011.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary:This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.
Physical Description:XVI, 281 p. online resource.
ISBN:9783642166150
DOI:10.1007/978-3-642-16615-0