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Using machine learning to determine the shared and unique risk factors for marijuana use among child-welfare versus community adolescents
OBJECTIVE: This study used machine learning (ML) to test an empirically derived set of risk factors for marijuana use. Models were built separately for child welfare (CW) and non-CW adolescents in order to compare the variables selected as important features/risk factors. METHOD: Data were from a Ti...
Autores principales: | Negriff, Sonya, Dilkina, Bistra, Matai, Laksh, Rice, Eric |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491564/ https://www.ncbi.nlm.nih.gov/pubmed/36129944 http://dx.doi.org/10.1371/journal.pone.0274998 |
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