ISBN: 9780367394240 - pattern recognition algorithms for data mining: scalability, knowledge discovery and soft granular computing (17 risultati)

Trade Paperback. Condizione: VG. used trade paperback edition. lightly shelfworn, corners perhaps slightly bumped. pages and binding are clean, straight and tight. there are no marks to the text or other serious flaws.

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Condizione: New.

Condizione: New. pp. 280.

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Condizione: New. pp. 280.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. pp. 280.

Paperback. Condizione: Brand New. 280 pages. 9.21x6.14x0.60 inches. In Stock.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 280 | Sprache: Englisch | Produktart: Bücher | This valuable text addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm. …

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This valuable text addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.…