An ensemble-based feature selection framework to select risk factors of childhood obesity for policy decision making.

ABSTRACT:

Background

The increasing prevalence of childhood obesity makes it essential to study the risk factors with a sample representative of the population covering more health topics for better preventive policies and interventions. It is aimed to develop an ensemble feature selection framework for large-scale data to identify risk factors of childhood obesity with good interpretability and clinical relevance.

Methods

We analyzed the data collected from 426,813 children under 18 during 2000-2019. A BMI above the 90th percentile for the children of the same age and gender was defined as overweight. An ensemble feature selection framework, Bagging-based Feature Selection framework integrating MapReduce (BFSMR), was proposed to identify risk factors. The framework comprises 5 models

SUBMITTER: Shi X 

PROVIDER: S-EPMC8293582 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature