Articles liés à Data Mining and Computational Intelligence
Synopsis
Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., "most students used to be profitable") and the patterns of the future (e.g., "students will be profitable").
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Data Mining and Computational Intelligence
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Physica-Verlag HD, 2001
ISBN 10 : 3790813710
ISBN 13 : 9783790813715
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Studies in Fuzziness and Soft Computing: Data Mining and Computational Intelligence
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Physica-Verlag, 2001
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ISBN 13 : 9783790813715
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Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9783790813715. N° de réf. du vendeur 5774259
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Data Mining and Computational Intelligence
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Physica-Verlag HD, 2001
ISBN 10 : 3790813710
ISBN 13 : 9783790813715
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive coverage of recent advances in the application of soft computing and fuzzy logic data miningAlso useful as a reference book in data mining, machine learning, fuzzy logic, and artificial intelligenceComprehensive coverage of recent a. N° de réf. du vendeur 5310333
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Data Mining and Computational Intelligence (Studies in Fuzziness and Soft Computing, Volume 68)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Data Mining and Computational Intelligence
Edité par
Physica-Verlag HD, 2001
ISBN 10 : 3790813710
ISBN 13 : 9783790813715
Neuf
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., 'most students used to be profitable') and the patterns of the future (e.g., 'students will be profitable'). N° de réf. du vendeur 9783790813715
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Data Mining and Computational Intelligence
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Physica-Verlag, Physica-Verlag HD, Physica Mrz 2001, 2001
ISBN 10 : 3790813710
ISBN 13 : 9783790813715
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., 'most students used to be profitable') and the patterns of the future (e.g., 'students will be profitable'). 356 pp. Englisch. N° de réf. du vendeur 9783790813715
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Data Mining and Computational Intelligence (Studies in Fuzziness and Soft Computing, Volume 68)
Vendeur : Best Price, Torrance, CA, Etats-Unis
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Etat : New. SUPER FAST SHIPPING. N° de réf. du vendeur 9783790813715
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Data Mining and Computational Intelligence
Edité par
Physica-Verlag HD Mär 2001, 2001
ISBN 10 : 3790813710
ISBN 13 : 9783790813715
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., 'most students used to be profitable') and the patterns of the future (e.g., 'students will be profitable').Physica Verlag, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch. N° de réf. du vendeur 9783790813715
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Data Mining and Computational Intelligence (Studies in Fuzziness and Soft Computing, Volume 68)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Etat : New. N° de réf. du vendeur ABLIING23Apr0316110061155
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Data Mining and Computational Intelligence
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. Print on Demand pp. 372 Illus. N° de réf. du vendeur 8375402
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