Fuzzy Modeling Tools for Data Mining and Knowledge Discovery

Earl Cox

530 pages, parution le 18/03/2005

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Résumé

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 instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.

Sommaire

Part one - concepts and issues
- Foundations and ideas
- Principal model types
- Approaches to model building
Part two - fuzzy systems
- Fundamental concepts of fuzzy logic
- Fundamental concepts of fuzzy systems
- Fuzzysql and intelligent queries
- Fuzzy clustering
- Fuzzy rule induction
Part three - evolutionary strategies
- Fundamental concepts of genetic algorithms
- Genetic resource scheduling optimization
- Genetic tuning of fuzzy models

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Morgan Kaufmann
Auteur(s)	Earl Cox
Parution	18/03/2005
Nb. de pages	530
Format	19 x 23,5
Couverture	Broché
Poids	1105g
Intérieur	Noir et Blanc
EAN13	9780121942755
ISBN13	978-0-12-194275-5