Early Detection of Sleep Disorders Using Ensemble Boosting and Classical ML with Lifestyle Data
Sleep disorders are increasingly prevalent in modern society, significantly impacting quality of life, productivity, and physical and mental health. This study distinguishes itself by evaluating six machine learning algorithms—Support Vector Machine (SVM), Naïve Bayes, K-Nearest Neighbor (KNN), XGBo...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Politeknik Negeri Batam
2026-04-01
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| coleção: | Journal of Applied Informatics and Computing |
| Assuntos: | |
| Acesso em linha: | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/12317 |
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