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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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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2016
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| 主題: | |
| オンライン･アクセス: | 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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