A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees

Arno de Caigny; Kristof Coussement; Koen W. de Bock

doi:10.1016/j.ejor.2018.02.009

Journal articles

A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees

Arno de Caigny ¹ Kristof Coussement ¹ Koen W. de Bock ²

1 IESEG - School of Management (LEM)

2 Audencia Recherche

Arno de Caigny ¹ AuthorId : 11156573
Author

Kristof Coussement ¹ AuthorId : 1697374
Author

Koen W. de Bock ² AuthorId : 11156574
Mail :
Author

1 IESEG - School of Management (LEM) (Socle de la Grande Arche 1 Parvis de la Défense, 92044 Paris La Défense Cedex - France) StructId : 460854

2 Audencia Recherche (8 route de la Jonelière BP 31222 44312 Nantes Cedex 3 - France) StructId : 130247

Audencia Business School (8 route de la Jonelière - 44312 Nantes Cedex 3 - France) StructId : 456031

Document type :

Journal articles

Domain :

Humanities and Social Sciences / Business administration

Statistics [stat] / Machine Learning [stat.ML]

Humanities and Social Sciences / Methods and statistics

Complete list of metadatas

https://hal-audencia.archives-ouvertes.fr/hal-01741661
Contributor : Koen W. de Bock <>
Submitted on : Friday, March 23, 2018 - 12:57:09 PM
Last modification on : Friday, July 26, 2019 - 11:58:03 AM

A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees

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A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees

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