Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data

We sought to verify the reliability of machine learning (ML) in developing diabetes prediction models by utilizing big data. To this end, we compared the reliability of gradient boosting decision tree (GBDT) and logistic regression (LR) models using data obtained from the Kokuho-database of the Osak...

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Detalles Bibliográficos
Autores principales: Seto, Hiroe, Oyama, Asuka, Kitora, Shuji, Toki, Hiroshi, Yamamoto, Ryohei, Kotoku, Jun’ichi, Haga, Akihiro, Shinzawa, Maki, Yamakawa, Miyae, Fukui, Sakiko, Moriyama, Toshiki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553945/
https://www.ncbi.nlm.nih.gov/pubmed/36220875
http://dx.doi.org/10.1038/s41598-022-20149-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553945/
https://www.ncbi.nlm.nih.gov/pubmed/36220875
http://dx.doi.org/10.1038/s41598-022-20149-z

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