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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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| Publicat a: | BMC Bioinformatics |
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| Autors principals: | , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2016
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4880828/ https://ncbi.nlm.nih.gov/pubmed/27230078 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-016-1084-8 |
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