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Структурні статистичні моделі: інструмент пізнання та моделювання
A promising class of models, namely, probabilistic models of dependences based on acyclic directed graphs (ADG), primarily of the Bayesian networks, is reviewed. The expressive and cognitive properties of the ADG models, their ability to convey a causal relationship are described. The role and place...
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| Main Authors: | , |
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| Format: | Article |
| Language: | rus |
| Published: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2018
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| Online Access: | http://journal.iasa.kpi.ua/article/view/127962 |
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| Summary: | A promising class of models, namely, probabilistic models of dependences based on acyclic directed graphs (ADG), primarily of the Bayesian networks, is reviewed. The expressive and cognitive properties of the ADG models, their ability to convey a causal relationship are described. The role and place of the Bayesian networks as a tool for analysis and deneralization of empirical data, their relation to logic and induction problem are shown in comparison with other approaches to cognition and model identification. |
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