Application and Analysis of Random Forest and Support Vector Classification in Risk Prediction of Childhood Obesity and Hyperuricemia

Yuhang Wang,1,&ast; Shuang Shi,1,&ast; Xinghua Wei,1 Yanjing Wu,1 Yunlong Shi,1 Jin Cai2 1Graduate School, Nantong University, Nantong, Jiangsu, People’s Republic of China; 2Department of Pediatrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu, People’s Republic of Ch...

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Bibliographic Details
Main Authors:	Wang Y, Shi S, Wei X, Wu Y, Shi Y, Cai J
Format:	Article
Language:	English
Published:	Dove Medical Press 2025-07-01
Series:	Diabetes, Metabolic Syndrome and Obesity
Subjects:	Childhood obesity hyperuricemia machine learning random forest support vector classification SHAP
Online Access:	https://www.dovepress.com/application-and-analysis-of-random-forest-and-support-vector-classific-peer-reviewed-fulltext-article-DMSO
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Application and Analysis of Random Forest and Support Vector Classification in Risk Prediction of Childhood Obesity and Hyperuricemia

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