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Approximate Learning of High Dimensional Bayesian Network Structures via Pruning of Candidate Parent Sets
Score-based algorithms that learn Bayesian Network (BN) structures provide solutions ranging from different levels of approximate learning to exact learning. Approximate solutions exist because exact learning is generally not applicable to networks of moderate or higher complexity. In general, appro...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597292/ https://www.ncbi.nlm.nih.gov/pubmed/33286911 http://dx.doi.org/10.3390/e22101142 |