Exploring father–adolescent closeness: A random forest approach.

Objective: This study demonstrates how machine learning, specifically random forest, can advance family science, particularly in studying father–child relationships. Background: Fatherhood research faces challenges with fathers' recruitment and retention, complex living arrangements, and lower respo...

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Publicado en:	Family Relations (John Wiley & Sons, Inc.) Vol. 74; no. 3; pp. 1216 - 1233
Autores principales:	Pace, Garrett T., Lee, Joyce Y., Ward, Kaitlin P., Chang, Olivia D.
Formato:	Artículo
Publicado:	John Wiley & Sons, Inc. Jul2025
Materias:	Father-child relationship Adolescence Artificial intelligence Machine learning Random forest algorithms
Acceso en línea:	Ver este registro en EBSCOhost