Discovering causal interactions using Bayesian network scoring and information gain

BACKGROUND: The problem of learning causal influences from data has recently attracted much attention. Standard statistical methods can have difficulty learning discrete causes, which interacting to affect a target, because the assumptions in these methods often do not model discrete causal relation...

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Detalles Bibliográficos
Autores principales: Zeng, Zexian, Jiang, Xia, Neapolitan, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4880828/
https://www.ncbi.nlm.nih.gov/pubmed/27230078
http://dx.doi.org/10.1186/s12859-016-1084-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4880828/
https://www.ncbi.nlm.nih.gov/pubmed/27230078
http://dx.doi.org/10.1186/s12859-016-1084-8

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