Quantile oriented sensitivity analysis with random forest based on pinball loss - Inria - Institut national de recherche en sciences et technologies du numérique
Pré-Publication, Document De Travail Année : 2024

Quantile oriented sensitivity analysis with random forest based on pinball loss

Résumé

Global Sensitivity Analysis (GSA) is an important tool to better understand the behavior of black box models. Among the numerous methods for GSA, variance-based approaches have received much attention. Only a few papers focus on Quantile Oriented Sensitivity Analysis (QOSA), which can help in analysing the behavior of the response at different quantile levels. Moreover, existing QOSA estimation methods have flaws: bias when input variables are dependent, loss of accuracy and efficiency as input space dimension increases. In this paper, we propose a new estimation procedure of QOSA indices based on the notion of projected random forest, with the initial random forest built from a criterion designed for quantiles: the pinball loss also known as quantile loss.
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hal-04606380 , version 1 (10-06-2024)

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  • HAL Id : hal-04606380 , version 1

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Ri Wang, Véronique Maume-Deschamps, Clémentine Prieur. Quantile oriented sensitivity analysis with random forest based on pinball loss. 2024. ⟨hal-04606380⟩
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