Generalized Additive Model with estimation of smooth functions using Neural Networks
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Updated
Mar 24, 2025 - Python
Generalized Additive Model with estimation of smooth functions using Neural Networks
This study proposes a diverse family of additive models that extend Generalized Additive Models to achieve both interpretability and predictive performance in forecasting. While preserving the stability of traditional GAMs, we develop Feature-wise Additive Models, Gradient Boosting Additive Models, and TabNet-based Neural Additive Models (TabNAM).
recurrent neural additive model
Interpretable GAM models for insurance pricing — EBM tariffs, Actuarial NAM, Pairwise Interaction Networks (PIN), exact Shapley values
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