Comparative performance of bagging and boosting ensemble models for predicting lumpy skin disease with multiclass-imbalanced data

Abstract Ensemble machine learning (ML) algorithms, such as bagging and boosting, are powerful decision-support tools that enhance disease prediction and risk management in the veterinary field. Lumpy Skin Disease (LSD) poses a significant threat to livestock health and results in substantial econom...

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Hlavní autoři:	Hagar F. Gouda, Fatma D. M. Abdallah
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2025-11-01
Edice:	Scientific Reports
Témata:	Bagging Ensemble learning Lumpy skin disease Vaccination Multi class imbalance SMOTE
On-line přístup:	https://doi.org/10.1038/s41598-025-23846-7
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