AI Research
Tabular Foundation Models vs Tuned Gradient Boosting for Telecom Churn: A Profit- and Calibration-Aware Evaluation
A profit- and calibration-aware comparison of two approaches to telecom churn prediction
Tabular foundation models (TFMs) predict from a labelled context in a single forward pass.
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ArXiv CS.AI
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ArXiv CS.AI
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Generated insight by OnAirToday AI
Telecom churn models can affect customer-retention decisions, so predictive performance alone may not capture their practical value. Comparing profit and calibration alongside tuned gradient boosting helps frame the evaluation around business impact and prediction reliability.
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