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portada Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering)
Type
Physical Book
Publisher
Author
Year
2014
Language
English
Pages
100
Format
Paperback
ISBN13
9781493905386
Edition No.
2014
Categories

Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering)

Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon (Author) · Springer · Paperback

Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) - Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon

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Synopsis "Proactive Data Mining With Decision Trees (Springerbriefs in Electrical and Computer Engineering) "

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.

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