Structure learning of Bayesian networks via data perturbation
Structure learning of Bayesian Networks (BNs) is an NP-hard problem, and the use of sub-optimal strategies is essential in domains involving many variables. One of them is to generate multiple approximate structures and then to reduce the ensemble to a representative structure. It is possible to use...
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| Format: | doctoralThesis |
| Language: | eng |
| Published: |
2018
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| Online Access: | https://doi.org/10.11606/T.18.2019.tde-19022019-134517 |
| Country: | Brazil |
| Oai: | oai:teses.usp.br:tde-19022019-134517 |