XGBOOST HYPERPARAMETER OPTIMIZATION USING RANDOMIZEDSEARCHCV FOR ACCURATE FOREST FIRE DROUGHT CONDITION PREDICTION

Climate change and increasing global temperatures have increased the frequency and intensity of forest fires, making fire risk evaluation increasingly important. This study aims to improve the accuracy of predicting forest fuel drought conditions (Drought Code) by using the XGBoost algorithm optimiz...

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Bibliographic Details

Main Authors:	Nur Alamsyah, Budiman Budiman, Titan Parama Yoga, R Yadi Rakhman Alamsyah
Format:	Artigo
Language:	Inglês
Published:	LPPM Nusa Mandiri 2024-09-01
Series:	Pilar Nusa Mandiri
Subjects:	forest fire prediction hyperparameter optimization xgboost
Online Access:	https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/5569
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