Neural network approach enhancing churn prediction with categorical encoding and standard scaling. [PDF]
Sci RepBhattacharjee B +7 more
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Social Network Analysis and Churn Prediction in Telecommunications Using Graph Theory. [PDF]
Entropy (Basel), 2020 Kostić SM, Simić MI, Kostić MV.
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Improving bank customer churn prediction with feature reduction using GA. [PDF]
Sci RepT N N, Pramod D.
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Churn prediction in telecommunication sector
, 2022 Tez (Yüksek Lisans) -- İstanbul Ticaret Üniversitesi -- Kaynakça var.
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Explainable AI-driven customer churn prediction: a multi-model ensemble approach with SHAP-based feature analysis. [PDF]
Front Artif IntellEl Attar A, El-Hajj M.
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Multimedia data-driven customer churn prediction using an enhanced extreme learning machine. [PDF]
Sci RepLiu YW, Wang J, Liu C.
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Deep learning for churn prediction
, 2022 The problem of churn prediction has been traditionally a field of study for marketing. However, in the wake of the technological advancements, more and more data can be collected to analyze the customers behaviors. This manuscript has been built in this frame, with a particular focus on machine learning. Thus, we first looked at the supervised learning
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Mitigating class imbalance in churn prediction with ensemble methods and SMOTE. [PDF]
Sci RepSuguna R +5 more
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A novel methodological approach to SaaS churn prediction using whale optimization algorithm. [PDF]
PLoS OneKotan M +5 more
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Customer churn prediction model based on hybrid neural networks. [PDF]
Sci RepLiu X, Xia G, Zhang X, Ma W, Yu C.
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