Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 172 pages. 9.00x7.25x0.75 inches. In Stock.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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In den WarenkorbZustand: New. pp. 172.
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: New.
Zustand: New. pp. 172.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. pp. 172.
Sprache: Englisch
Verlag: Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128116544 ISBN 13: 9780128116548
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
EUR 56,86
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In den WarenkorbPaperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.
Anbieter: Brook Bookstore On Demand, Napoli, NA, Italien
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In den WarenkorbZustand: new. Questo è un articolo print on demand.
Sprache: Englisch
Verlag: Elsevier, München, Elsevier, 2016
ISBN 10: 0128116544 ISBN 13: 9780128116548
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics. Englisch.
Sprache: Englisch
Verlag: Elsevier, München, Elsevier, 2016
ISBN 10: 0128116544 ISBN 13: 9780128116548
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.