Applied genetic programming and machine learning / Hitoshi Iba, Topon Kumar Paul, Yoshihiko Hasegawa.
Material type: TextSeries: The CRC Press international series on computational intelligencePublication details: Boca Raton : CRC Press, c2010.Description: xxvi, 327 p. : ill. ; 25 cmISBN:- 9781439803691 (hc : alk. paper)
- 006.31 22
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
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Books | Main library General Stacks | 006.31 / IB.A 2010 (Browse shelf(Opens below)) | 1 | Available | 007539 |
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006.31 / CH.L 1998 Learning from data : | 006.31 / CL.P 2009 Principles and theory for data mining and machine learning / | 006.31 / CO.M 2008 Machine learning techniques for multimedia : | 006.31 / IB.A 2010 Applied genetic programming and machine learning / | 006.31 / IN. M 2010 Multiple classifier systems : | 006.31 / PE.M 2009 Machine learning and data mining in pattern recognition : | 006.31 / RO.F 2011 A first course in machine learning / |
Includes bibliographical references and index.
Genetic Programming -- Numerical Approach to Genetic Programming -- Classification by Ensemble of Genetic Programming Rules -- Probabilistic Program Evolution.
Reflecting rapidly developing concepts and newly emerging paradigms in intelligent machines, this text is the first to integrate genetic programming and machine learning techniques to solve diverse real-world tasks.These tasks include financial data prediction, day-trading rule development; and bio-marker selection. Written by a leading authority, this text will teach readers how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the search process through the design of objective fitness functions, and examine the search performance of the evolutionary system. All source codes and GUIs are available for download from the author's website
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