A framework integrating explainable AI for feature attribution, survival analysis for time-to-churn modeling, and RFM profiling for behavioral segmentation to support interpretable retention strategies in online retail.
Toward safer highways, application of xgboost and shap for real-time accident detection and feature analysis
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Explainability, risk modeling, and segmentation based customer churn analytics for personalized retention in e-commerce
A framework integrating explainable AI for feature attribution, survival analysis for time-to-churn modeling, and RFM profiling for behavioral segmentation to support interpretable retention strategies in online retail.