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pro vyhledávání: '"Flachaire, Emmanuel"'
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
Many problems ask a question that can be formulated as a causal question: "what would have happened if...?" For example, "would the person have had surgery if he or she had been Black?" To address this kind of questions, calculating an average treatm
Externí odkaz:
http://arxiv.org/abs/2301.07755
Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes or uninterpretable models which has raised concerns from practitioners and regulators. As an alternative, we propose in this paper to u
Externí odkaz:
http://arxiv.org/abs/2203.11691
The Pareto model is very popular in risk management, since simple analytical formulas can be derived for financial downside risk measures (Value-at-Risk, Expected Shortfall) or reinsurance premiums and related quantities (Large Claim Index, Return Pe
Externí odkaz:
http://arxiv.org/abs/1912.11736
Recently, Broido & Clauset (2019) mentioned that (strict) Scale-Free networks were rare, in real life. This might be related to the statement of Stumpf, Wiuf & May (2005), that sub-networks of scale-free networks are not scale-free. In the later, tho
Externí odkaz:
http://arxiv.org/abs/1905.10267
Akademický článek
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Publikováno v:
In Econometrics and Statistics February 2022
Econometrics and machine learning seem to have one common goal: to construct a predictive model, for a variable of interest, using explanatory variables (or features). However, these two fields developed in parallel, thus creating two different cultu
Externí odkaz:
http://arxiv.org/abs/1708.06992
Akademický článek
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