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210123 ||| eng |
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|a 1280961295
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|a 9781280961298
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|a 9786610961290
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|a 9780080470597
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|a 0080470599
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|a QA9.64
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|a Cox, Earl
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| 245 |
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|a Fuzzy modeling and genetic algorithms for data mining and exploration
|c Earl Cox
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| 260 |
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|a San Francisco, CA
|b Elsevier/Morgan Kaufmann
|c 2005
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| 300 |
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|a xxi, 530 pages
|b illustrations
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|a Part I Concepts and Issues; Chapter 1 Foundations and Ideas; Chapter 2 Principal Model Types; Chapter 3 Approaches to Model Building; Part II Fuzzy Systems; Chapter 4 Fundamental Concepts of Fuzzy Logic; Chapter 5 Fundamental Concepts of Fuzzy Systems; Chapter 6 Fuzzy SQL and Intelligent Queries; Chapter 7 Fuzzy Clustering; Chapter 8 Fuzzy Rule Induction; Part III Evolutionary Strategies; Chapter 9 Fundamental Concepts of Genetic Algorithms; Chapter 10 Genetic Resource Scheduling Optimization; Chapter 11 Genetic Tuning of Fuzzy Models; Index
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|a Includes bibliographical references and index
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| 653 |
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|a Data mining / fast
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|a Data Mining
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|a Fuzzy logic / fast
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| 653 |
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|a Genetic algorithms / http://id.loc.gov/authorities/subjects/sh92002377
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| 653 |
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|a Algorithmes génétiques
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| 653 |
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|a Genetic algorithms / fast
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| 653 |
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|a Logique floue
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| 653 |
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
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|a Fuzzy logic / http://id.loc.gov/authorities/subjects/sh93006704
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| 653 |
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|a Exploration de données (Informatique)
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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|a The Morgan Kaufmann series in data management systems
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|z 9780080470597
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| 776 |
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|z 0080470599
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| 776 |
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|z 9780121942755
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| 776 |
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|z 0121942759
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| 856 |
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|u https://learning.oreilly.com/library/view/~/9780080470597/?ar
|x Verlag
|3 Volltext
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|a 006.3/12
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| 520 |
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|a Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you'll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You don't need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed inst
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