Related references
Note: Only part of the references are listed.Evaluation of customer behavior with temporal centrality metrics for churn prediction of prepaid contracts
Laura Calzada-Infante et al.
EXPERT SYSTEMS WITH APPLICATIONS (2020)
Metalearners for estimating heterogeneous treatment effects using machine learning
Soren R. Kunzel et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)
Modeling and forecasting time series of precious metals: a new approach to multifractal data
Emrah Oral et al.
FINANCIAL INNOVATION (2019)
Customer Churn Prediction with Feature Embedded Convolutional Neural Network: An Empirical Study in the Internet Funds Industry
Chongren Wang et al.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (2019)
A big data analytics model for customer churn prediction in the retiree segment
Farid Shirazi et al.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT (2019)
Evaluation of forecasting methods from selected stock market returns
M. Mallikarjuna et al.
FINANCIAL INNOVATION (2019)
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Stefan Wager et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2018)
Profit-Based Model Selection for Customer Retention Using Individual Customer Lifetime Values
Maria Oskarsdottir et al.
BIG DATA (2018)
Profit maximizing logistic model for customer churn prediction using genetic algorithms
Eugen Stripling et al.
SWARM AND EVOLUTIONARY COMPUTATION (2018)
Behavioral attributes and financial churn prediction
Erdem Kaya et al.
EPJ DATA SCIENCE (2018)
Dropout and retention of undergraduate students in management: a study at a Brazilian Federal University
Francisco Jose da Costa et al.
RAUSP MANAGEMENT JOURNAL (2018)
Developing a prediction model for customer churn from electronic banking services using data mining
Abbas Keramati et al.
FINANCIAL INNOVATION (2016)
Profit-based feature selection using support vector machines - General framework and an application for customer retention
Sebastian Maldonado et al.
APPLIED SOFT COMPUTING (2015)
Social network analysis for customer churn prediction
Wouter Verbeke et al.
APPLIED SOFT COMPUTING (2014)
Development and application of consumer credit scoring models using profit-based V classification measures
Thomas Verbraken et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2014)
Analyzing the applications of customer lifetime value (CLV) based on benefit segmentation for the banking sector
Mohammad Safari Kahreh et al.
2ND WORLD CONFERENCE ON BUSINESS, ECONOMICS AND MANAGEMENT (2014)
A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models
Thomas Verbraken et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2013)
A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data
Zhen-Yu Chen et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2012)
New insights into churn prediction in the telecommunication sector: A profit driven data mining approach
Wouter Verbeke et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2012)
Handling class imbalance in customer churn prediction
J. Burez et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Measuring classifier performance: a coherent alternative to the area under the ROC curve
David J. Hand
MACHINE LEARNING (2009)
A stepwise AIC method for variable selection in linear regression
Toshie Yamashita et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS (2007)
Defection detection: Measuring and understanding the predictive accuracy of customer churn models
SA Neslin et al.
JOURNAL OF MARKETING RESEARCH (2006)
Customer attrition analysis for financial services using proportional hazard models
D Van den Poel et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2004)
Turning telecommunications call details to churn prediction: a data mining approach
CP Wei et al.
EXPERT SYSTEMS WITH APPLICATIONS (2002)
Automated cellular modeling and prediction on a large scale
P Datta et al.
ARTIFICIAL INTELLIGENCE REVIEW (2000)
Understanding the customer base of service providers: An examination of the differences between switchers and stayers
J Ganesh et al.
JOURNAL OF MARKETING (2000)
Share Paper
