An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry. [PDF]
PeerJ Comput Sci, 2022 Fakhar Bilal S +4 more
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Utilizing data sampling techniques on algorithmic fairness for customer churn prediction with data imbalance problems. [PDF]
F1000Res, 2021 Maw M, Haw SC, Ho CK.
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JOIV: International Journal on Informatics VisualizationThis study aims to examine the effect of customer experience on customer retention at DQLab Telco, using machine learning techniques to predict customer churn.
Kusnawi Kusnawi +5 more
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Applying CHAID for logistic regression diagnostics and classification accuracy improvement [PDF]
In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: 1. How to automatically detect segments in which the
Antipov, Evgeny, Pokryshevskaya, Elena
core
Predictive Modeling for Customer Churn
Customer churn is a major concern for the banking industry, where retaining existing customers is often more profitable than acquiring new ones. With increasing competition from digital banks and fintech startups, it has become vital for traditional banks to proactively identify customers who are likely to leave.
Dr. AS Arunachalam, B Sathya Moorthy
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Telco Customer Churn Prediction
Highlights in Science, Engineering and TechnologyIn recognizing the significance of retaining current consumers to thrive in this competitive landscape, this paper aims to predict customers' churn probability based on the background and behaviors of previous customers. The paper utilizes churn probability as a proactive means to identify customers at a high risk of leaving, serving as a reference for
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A hybrid feature selection framework for dimensionality-optimized customer churn prediction. [PDF]
Sci RepOmar AS, Ogada K, Tole K.
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Customer churn prediction in privacy-preserving HashCode-based security abstractions. [PDF]
Sci RepMunshi A.
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A novel hybrid deep learning framework for customer churn prediction using RFM and embedding clustering. [PDF]
Sci RepIbrahim S +3 more
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Customer Churn Analysis and Prediction [PDF]
International Journal of Computer Applications Technology and Research, 2019 Aditya Kulkarni +3 more
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