The paper presents model based on fuzzy methods for churn prediction in retail banking. The study was done on the real, anonymised data of 5000 clients of a retail bank. Real data are great strength of the study, as a lot of studies often use old, irrelevant or artificial data. Canonical discriminant analysis was applied to reveal variables that provide maximal separation between clusters of ch...

0957-4174/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.eswa.2008.05.027 * Corresponding author. Tel.: +32 9 264 89 80; fax: E-mail address: [email protected] (D. Va URL: http://www.crm.UGent.be (D. Van den Poel). Customer churn is often a rare event in service industries, but of great interest and great value. Until recently, however, class imbalance has not received much attent...

Practical applications of machine learning often involve successive training iterations with changes to features and training examples. Ideally, changes in the output of any new model should only be improvements (wins) over the previous iteration, but in practice the predictions may change neutrally for many examples, resulting in extra net-zero wins and losses, referred to as unnecessary churn...

The diversity and specificities of today’s businesses have leveraged a wide range prediction techniques. In particular, churn is major economic concern for many companies. purpose this study to draw general guidelines from benchmark supervised machine learning techniques in association with widely used data sampling approaches on publicly available datasets the context prediction. Choosing prio...