Leveraging Random Forests explainability for predictive modeling of children's conduct problems: insights from individual and family factors

Leveraging Random Forests explainability for predictive modeling of children's conduct problems: insights from individual and family factors

Conduct problems are among the most complex, impairing, and prevalent challenges affecting the mental health of children and adolescents. Due to their multifaceted nature, it is important to develop predictive models that capture the intricate interactions among contributing factors. This longitudin...

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Bibliographic Details
Main Authors: Estrella Romero, Jaime González-González, María Álvarez-Voces, Enrique Costa-Montenegro, Beatriz Díaz-Vázquez, Andrea Busto-Castiñeira, Paula Villar, Laura López-Romero
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Public Health
Subjects:
conduct problems
childhood
Random Forest
family variables
individual variables
explainability
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1526413/full
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