Tabular foundation models excel on tiny- to medium-sized IID data but are outperformed by traditional tree-based and deep learning models on non-IID, large, and high-dimensional datasets, based on evaluations across 11 models and 142 datasets in the new BeyondArena benchmark.
Model comparison and calibration assessment: User guide for consistent scoring functions in machine learning and actuarial practice.arXiv preprint arXiv:2202.12780, 2022
2 Pith papers cite this work. Polarity classification is still indexing.
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Boosting trees test necessary conditions for calibration and auto-calibration of regression models, shown powerful on a large insurance dataset.
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Beyond IID: How General Are Tabular Foundation Models, Really?
Tabular foundation models excel on tiny- to medium-sized IID data but are outperformed by traditional tree-based and deep learning models on non-IID, large, and high-dimensional datasets, based on evaluations across 11 models and 142 datasets in the new BeyondArena benchmark.
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Assessing model calibration with boosting trees
Boosting trees test necessary conditions for calibration and auto-calibration of regression models, shown powerful on a large insurance dataset.