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Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 102 pages. 9.00x6.00x0.25 inches. In Stock.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Proactive Data Mining with Decision Trees | Haim Dahan (u. a.) | Taschenbuch | SpringerBriefs in Electrical and Computer Engineering | x | Englisch | 2014 | Springer | EAN 9781493905386 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer New York Feb 2014, 2014
ISBN 10: 1493905384 ISBN 13: 9781493905386
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students. 100 pp. Englisch.
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Condition: New. Print on Demand pp. 100 20 Illus.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 100.
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasThis book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but al.
Language: English
Published by Springer, Springer Feb 2014, 2014
ISBN 10: 1493905384 ISBN 13: 9781493905386
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 100 pp. Englisch.