Proactive Data Mining with Decision Trees (Record no. 52231)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03140nam a22005295i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-1-4939-0539-3 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200420220226.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140214s2014 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781493905393 |
| -- | 978-1-4939-0539-3 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.312 |
| 100 1# - AUTHOR NAME | |
| Author | Dahan, Haim. |
| 245 10 - TITLE STATEMENT | |
| Title | Proactive Data Mining with Decision Trees |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | X, 88 p. 20 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | SpringerBriefs in Electrical and Computer Engineering, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Proactive Data Mining: A General Approach -- Proactive Data Mining Using Decision Trees -- Proactive Data Mining in the Real World: Case Studies -- Sensitivity Analysis of Proactive Data Mining -- Conclusions. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cohen, Shahar. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Rokach, Lior. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Maimon, Oded. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4939-0539-3 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | New York, NY : |
| -- | Springer New York : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information storage and retrieval. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information Storage and Retrieval. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information Systems Applications (incl. Internet). |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2191-8112 |
| 912 ## - | |
| -- | ZDB-2-SCS |
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