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Found 2 papers, 1 papers with code
Calibrated Explanations for Regression
This paper introduces an extension of a feature importance explanation method, Calibrated Explanations, previously only supporting classification, with support for standard regression and probabilistic regression, i. e., the probability that the target is above an arbitrary threshold.
Well-Calibrated Probabilistic Predictive Maintenance using Venn-Abers
In the experiments, we apply Venn-Abers calibration to decision trees, random forests and XGBoost models, showing how both overconfident and underconfident models are corrected.
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