NDLI: Transfer Ensemble Model for Customer Churn Prediction with Imbalanced Class Distribution

Content Provider	IEEE Xplore Digital Library
Author	Yuan Wang Jin Xiao
Copyright Year	2011
Abstract	Customer churn prediction is an important issue in customer relationship management. The class distribution of customer data is often imbalanced, which may affect the performance of churn prediction model greatly. This paper combines transfer learning and multiple classifiers ensemble, and proposes a transfer ensemble model for imbalanced data (TEMID). This method focuses on using transfer learning and sampling to enlarge the available training set and balance it respectively. What's more, it also uses multiple classifiers ensemble method to implement the classification. The performance of TEMID and some existing transfer learning algorithms are compared in two class imbalanced datasets. The results show that the TEMID methods can actually improve the performance of the customer churn prediction.
Starting Page	177
Ending Page	181
File Size	476720
Page Count	5
File Format	PDF
ISBN	9781457714191
DOI	10.1109/ICM.2011.397
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Customer churn prediction Accuracy Multiple classifiers ensemble Transfer ensemble model Transfer learning Machine learning Predictive models Prediction algorithms Educational institutions Imbalanced class distribution Data models
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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