Proactive data mining with decision trees [electronic resource] / Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon.
By: Dahan, Haim [author.]
.
Contributor(s): Cohen, Shahar [author.] | Rokach, Lior [author.].
Series: SpringerBriefs in electrical and computer engineering: Publisher: New York : Springer, [2014]Copyright date: ©2014Description: x, 88 pages : illustrations (black and white).Content type: text | still image Media type: computer Carrier type: online resourceISBN: 9781493905393 (e-book).Subject(s): Data mining | Decision trees | Computers and IT | Graphical & digital media applications | Data mining | Information retrieval | Information technology: general issues | System administration | Storage media & peripheralsGenre/Form: Electronic books.Online resources: View this item online Also available in printed form ISBN 9781493905386Summary: 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.
| Item type | Current library | Call number | Status | Notes | Date due | Barcode | |
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e-book
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Digital Library Digital Library Browns ebook | 006.312 EBOOK (Browse shelf(Opens below)) | Not for loan | Use your City Account login details. | 3230081858 |
Includes bibliographical references.
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.
Also available in printed form ISBN 9781493905386
Electronic reproduction. Askews and Holts. Mode of access: World Wide Web.
