Classification of Obesity among South African Female Adolescents: Comparative Analysis of Logistic Regression and Random Forest Algorithms.

ABSTRACT:

Background

This study evaluates the performance of logistic regression (LR) and random forest (RF) algorithms to model obesity among female adolescents in South Africa.

Methods

Data was analysed on 375 females aged 15-17 from the South African National Health and Nutrition Examination Survey 2011/2012. The primary outcome was obesity, defined as body mass index (BMI) ≥ 30 kg/m². A total of 31 explanatory variables were included, ranging from socio-economic, demographic, family history, dietary and health behaviour. RF and LR models were run using imbalanced data as well as after oversampling, undersampling, and hybrid sampling of the data.

Results

Using the imbalanced data, the RF model performed better with higher precision, recall, F1 score, and balanced

SUBMITTER: Sewpaul R 

PROVIDER: S-EPMC10815679 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature