Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation
Learning the structure of Bayesian networks from data is known to be a computationally challenging, NP-hard problem. The literature has long investigated how to perform structure learning from data containing large numbers of variables, following a general interest in high-dimensional applications (...
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| Published in: | Statistics and computing Vol. 29; no. 5; pp. 1095 - 1108 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Springer US
11.09.2019
Springer Nature B.V |
| Subjects: | |
| ISSN: | 0960-3174, 1573-1375 |
| Online Access: | Get full text |
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