Proactive Data Mining with Decision Trees
Dahan, Haim, Cohen, Shahar, Rokach, Lior, Maimon, Oded
Produktnummer:
183ce0df772f3c4573a1305c9b8b4bf571
| Autor: | Cohen, Shahar Dahan, Haim Maimon, Oded Rokach, Lior |
|---|---|
| Themengebiete: | active learning data mining decision trees maximal-utility splitting criterion optimization |
| Veröffentlichungsdatum: | 15.02.2014 |
| EAN: | 9781493905386 |
| Sprache: | Englisch |
| Seitenzahl: | 88 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer US |
Produktinformationen "Proactive Data Mining with Decision Trees"
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.
Sie möchten lieber vor Ort einkaufen?
Sie haben Fragen zu diesem oder anderen Produkten oder möchten einfach gerne analog im Laden stöbern? Wir sind gerne für Sie da und beraten Sie auch telefonisch.
Juristische Fachbuchhandlung
Georg Blendl
Parcellistraße 5 (Maxburg)
8033 München
Montag - Freitag: 8:15 -18 Uhr
Samstags geschlossen