The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Predicting customer retention and profitability by using random forests and regression forests techniques
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Citations
Cites
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Determinants of Long-Term Orientation in Buyer-Seller Relationships
Ganesan, S. (1994) · Journal of Marketing · doi:10.1177/002224299405800201 · Cited by 6,741
Ganesh, J., Arnold, M. J., & Reynolds, K. E. (2000) · Journal of Marketing · doi:10.1509/jmkg.64.3.65.18028 · Cited by 1,305
Kamakura, W. A., Ramaswami, S. N., & Srivastava, R. K. (1991) · International Journal of Research in Marketing · doi:10.1016/0167-8116(91)90030-b · Cited by 240
Cited by
Data mining for credit card fraud: a comparative study
Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.08.008 · Cited by 1,108
Verbeke, W., Dejaeger, K., Martens, D., Hur, J., & Baesens, B. (2012) · European Journal of Operational Research · doi:10.1016/j.ejor.2011.09.031 · Cited by 462
Forecasting Stock Index Movement: A Comparison of Support Vector Machines and Random Forest
Kumar, M., & Thenmozhi, M. (2006) · doi:10.2139/ssrn.876544 · Cited by 244
Saradhi, V. V., & Palshikar, G. K. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.07.134 · Cited by 188
Automated trading with performance weighted random forests and seasonality
Booth, A., Gerding, E., & McGroarty, F. (2014) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.12.009 · Cited by 154
An effective hybrid learning system for telecommunication churn prediction
Huang, Y., & Kechadi, T. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.04.020 · Cited by 90
Random Forests for Uplift Modeling: An Insurance Customer Retention Case
Guelman, L., Guillén, M., & Pérez-Marín, A. M. (2012) · Lecture Notes in Business Information Processing · doi:10.1007/978-3-642-30433-0_13 · Cited by 61
de la Llave, M. Á., López, F. A., & Angulo, A. (2019) · Scandinavian Actuarial Journal · doi:10.1080/03461238.2018.1531781 · Cited by 21
Metadata
- Authors
- LARIVIERE, B., & VANDENPOEL, D.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2005-08
- Volume
- 29
- Issue
- 2
- Pages
- 472-484
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2140301981
- Cited by
- 308
- References
- 4
- FWCI
- 33.06
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
