Three Categories Customer Churn Prediction Based on the Adjusted Real Adaboost

DOI10.1080/03610918.2011.589732zbMath1227.62115OpenAlexW2032502034MaRDI QIDQ3102903

Xiu-Quan Qiao, Miao Liu, Wang-li Xu

Publication date: 25 November 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.589732

zbMATH Keywords

customer heterogeneityunbalanced data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics (62P99) Marketing, advertising (90B60)

Cites Work

• Boosting algorithms: regularization, prediction and model fitting
• Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
• Improved boosting algorithms using confidence-rated predictions
• Adaptive Weighted Learning for Unbalanced Multicategory Classification

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