ШВИДКИЙ АЛГОРИТМ ВИВЕДЕННЯ СТРУКТУР БАЙЄСОВИХ МЕРЕЖ З ДАНИХ
We have developed a new constraint-based algorithm for learning dependency struc-tures from data. Novelty of proposed algorithm comes from implementing rules of inductive inference acceleration, which can radically reduce a searching space for skeleton inference. We have demonstrated that proposed a...
Збережено в:
| Дата: | 2025 |
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| Автори: | , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
V.M. Glushkov Institute of Cybernetics of NAS of Ukraine
2025
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| Онлайн доступ: | https://jais.net.ua/index.php/files/article/view/598 |
| Теги: |
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| Назва журналу: | Problems of Control and Informatics |
Репозитарії
Problems of Control and Informatics| Резюме: | We have developed a new constraint-based algorithm for learning dependency struc-tures from data. Novelty of proposed algorithm comes from implementing rules of inductive inference acceleration, which can radically reduce a searching space for skeleton inference. We have demonstrated that proposed algorithm learns Bayesian nets (of moderate density) multiple times faster than well-known PC algorithm. |
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