Overview
- Book introduces many original ideas
- Significant contribution to the field
- Authors detail collaborations in biological and data mining applications
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Multiobjective Genetic Algorithms for Clustering
Book Subtitle: Applications in Data Mining and Bioinformatics
Authors: Ujjwal Maulik, Sanghamitra Bandyopadhyay, Anirban Mukhopadhyay
DOI: https://doi.org/10.1007/978-3-642-16615-0
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-16614-3Published: 02 September 2011
Softcover ISBN: 978-3-642-43963-6Published: 23 November 2014
eBook ISBN: 978-3-642-16615-0Published: 01 September 2011
Edition Number: 1
Number of Pages: XVI, 281
Topics: Artificial Intelligence, Computational Biology/Bioinformatics, Data Mining and Knowledge Discovery, Computational Intelligence