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pro vyhledávání: '"Machado, Agathe Fernandes"'
In this paper, we link two existing approaches to derive counterfactuals: adaptations based on a causal graph, as suggested in Ple\v{c}ko and Meinshausen (2020) and optimal transport, as in De Lara et al. (2024). We extend "Knothe's rearrangement" Bo
Externí odkaz:
http://arxiv.org/abs/2408.03425
Autor:
Machado, Agathe Fernandes, Charpentier, Arthur, Flachaire, Emmanuel, Gallic, Ewen, Hu, François
In binary classification tasks, accurate representation of probabilistic predictions is essential for various real-world applications such as predicting payment defaults or assessing medical risks. The model must then be well-calibrated to ensure ali
Externí odkaz:
http://arxiv.org/abs/2408.03421
Autor:
Machado, Agathe Fernandes, Charpentier, Arthur, Flachaire, Emmanuel, Gallic, Ewen, Hu, François
The assessment of binary classifier performance traditionally centers on discriminative ability using metrics, such as accuracy. However, these metrics often disregard the model's inherent uncertainty, especially when dealing with sensitive decision-
Externí odkaz:
http://arxiv.org/abs/2402.07790
Driven by an increasing prevalence of trackers, ever more IoT sensors, and the declining cost of computing power, geospatial information has come to play a pivotal role in contemporary predictive models. While enhancing prognostic performance, geospa
Externí odkaz:
http://arxiv.org/abs/2401.16197