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...
Gespeichert in:
| Datum: | 2018 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Russisch |
| Veröffentlicht: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2018
|
| Online Zugang: | http://journal.iasa.kpi.ua/article/view/127962 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | System research and information technologies |
Institution
System research and information technologies| Zusammenfassung: | 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. |
|---|