9783642058608 - classification and modeling with linguistic information granules: advanced approaches to linguistic data mining (advanced information processing) de ishibuchi, hisao; nakashima, tomoharu; nii, manabu (11 resultados)

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Taschenbuch. Condición: Neu. Classification and Modeling with Linguistic Information Granules | Advanced Approaches to Linguistic Data Mining | Hisao Ishibuchi (u. a.) | Taschenbuch | Advanced Information Processing | xii | Englisch | 2010 | Springer | EAN 9783642058608 | Verantwortliche Person für die EU: Springer Verlag GmbH,…Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonl…inear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are comp…licated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability. 320 pp. Englisch.

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Clear illustration how fuzzy logic and neural networks are utilized for extracting linguistic knowledgeMany figures and simulation resultsReference for researchers and practitioners in data mining, fuzzy systems and n…eural networksBe.

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Condición: New. Print on Demand pp. 320 217 Illus.

Idioma: Inglés
Editorial: Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2010, 2010
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complica…ted and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.

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Condición: New. PRINT ON DEMAND pp. 320.