Modified resampling strategy for extreme values in imbalanced air pollution data using moving block bootstrapping approach with relevance weighting (MBB-RW)

Abstract Air pollution datasets typically exhibit a right-skewed distribution. These conditions are caused by the presence of extreme events leading to imbalanced data distribution. This imbalanced regression poses a notable challenge in predictive modeling, as the models tend to be biased towards f...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Mahiran Muhammad, Ahmad Zia Ul-Saufie, Noor Fadhilah Ahmad Radi, Norazian Mohamed Noor, Arief Gusnanto
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Nature Portfolio 2025-12-01
Schriftenreihe:	Scientific Reports
Schlagworte:	Particulate matter 10 (PM10) Extreme events Imbalanced data Moving block bootstrapping (MBB) Moving block bootstrapping with relevance weighting (MBB-RW) Extreme gradient boosting (XGBoost)
Online-Zugang:	https://doi.org/10.1038/s41598-025-28416-5
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