Time series causal relationships discovery through feature importance and ensemble models

Time series causal relationships discovery through feature importance and ensemble models

Abstract Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data available in many areas, Machine Learning algorithms used for forecasting have become more compl...

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Bibliographic Details
Main Authors: Manuel Castro, Pedro Ribeiro Mendes Júnior, Aurea Soriano-Vargas, Rafael de Oliveira Werneck, Maiara Moreira Gonçalves, Leopoldo Lusquino Filho, Renato Moura, Marcelo Zampieri, Oscar Linares, Vitor Ferreira, Alexandre Ferreira, Alessandra Davólio, Denis Schiozer, Anderson Rocha
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-37929-w

Internet

https://doi.org/10.1038/s41598-023-37929-w

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