Predicting credit card customer churn in banks using data mining
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Manolis Maragoudakis & Dimitrios Serpanos, 2016. "Exploiting Financial News and Social Media Opinions for Stock Market Analysis using MCMC Bayesian Inference," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 589-622, April.
- Owen P. Hall Jr. & Darrol J. Stanley, 2012. "A comparative modelling analysis of firm performance," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 4(1), pages 43-56.
- Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
- repec:spr:fininn:v:2:y:2016:i:1:d:10.1186_s40854-016-0029-6 is not listed on IDEAS
- Vera Miguéis & Dirk Poel & Ana Camanho & João Falcão e Cunha, 2012.
"Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences,"
Advances in Data Analysis and Classification,
Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 337-353, December.
- V. L. Miguéis & D. Van Den Poel & A.S. Camanho & Joao Falcao E Cunha, 2012. "Predicting Partial Customer Churn Using Markov for Discrimination for Modeling First Purchase Sequences," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/806, Ghent University, Faculty of Economics and Business Administration.
- Ballings, Michel & Van den Poel, Dirk, 2015. "CRM in social media: Predicting increases in Facebook usage frequency," European Journal of Operational Research, Elsevier, vol. 244(1), pages 248-260.
More about this item
Keywordscredit cards; credit card churn; data mining; churn prediction; multilayer perceptron; MLP; logistic regression; decision tree; random forest; radial basis function; RBF neural networks; support vector machine; SVM; synthetic minority oversampling technique; SMOTE; undersampling; oversampling; expert systems.;
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:injdan:v:1:y:2008:i:1:p:4-28. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Darren Simpson). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.