The morgan kaufmann series in data management systems - 9780121942755 - fuzzy modeling and genetic algorithms for data mining and exploration (the morgan kaufmann series in data management systems) di cox, earl (19 risultati)

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1st ed. 19 x 23 cm. 530 pages. Paperback. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

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Soft cover. Condizione: New. 1st Edition. Morgan Kaufmann, 2005. 1st Edition. XXI+530 pages New Soft cover. 7x10x1.25 in. be41.

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Tapa Blanda. Condizione: Muy bien. Tapa blanda. Ilustrado. 9780121942755. Morgan Kaufmann. Estados Unidos. 2005. 24x19 centímetros. 530 páginas. Tapa blanda. Estado=Muy bien. Inglés.

Condizione: New. pp. 556.

Condizione: New. pp. 556 Illus.

Condizione: New. Suitable for analysts, engineers and managers involved in developing data mining models in business and government, this work helps you to understand the trade-offs implicit in various models and model architectures. It provides coverage of fuzzy SQL queryi.

Taschenbuch. Condizione: Neu. Neuware - 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. Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems Helps you to understand the trade-offs implicit in various models and model architectures Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem Presents examples in C, C++, Java, and easy-to-understand pseudo-code Extensive online component, including sample code and a complete data mining workbench.…

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