Health Risk Classification Using XGBoost with Bayesian Hyperparameter Optimization

Health Risk Classification Using XGBoost with Bayesian Hyperparameter Optimization

Health risk classification is important. However, health risk classification is challenging to address using conventional analytical techniques. The XGBoost algorithm offers many advantages over the traditional methods for risk classification. Hyperparameter Optimization (HO) of XGBoost is critical...

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Bibliographic Details
Main Authors: Syaiful Anam, Imam Nurhadi Purwanto, Dwi Mifta Mahanani, Feby Indriana Yusuf, Hady Rasikhun
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2025-06-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Subjects:
health risk classification
hyperparameters
optimization
xgboost
Online Access:https://jurnal.iaii.or.id/index.php/RESTI/article/view/6307
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