| Description |
1 online resource (xxi, 530 pages) : illustrations |
| Series |
The Morgan Kaufmann series in data management systems |
|
Morgan Kaufmann series in data management systems.
|
| Bibliography |
Includes bibliographical references and index. |
| Contents |
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. |
| Summary |
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. |
| Language |
English. |
| Subject |
Data mining.
|
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Fuzzy logic.
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Genetic algorithms.
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|
Exploration de données (Informatique) |
|
Logique floue. |
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Algorithmes génétiques. |
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Data mining |
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Fuzzy logic |
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Genetic algorithms |
| Other Form: |
Print version: Cox, Earl. Fuzzy modeling and genetic algorithms for data mining and exploration. San Francisco, CA : Elsevier/Morgan Kaufmann, ©2005 (DLC) 2004061901 |
| ISBN |
9780080470597 (electronic bk.) |
|
0080470599 (electronic bk.) |
|
1280961295 |
|
9781280961298 |
|
9786610961290 |
|
6610961298 |
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