Statements (34)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:Causal_model
gptkb:Probabilistic_graphical_model |
| gptkbp:appliesTo |
gptkb:artificial_intelligence
Statistics Epidemiology Machine learning Econometrics |
| gptkbp:basedOn |
gptkb:Bayesian_networks
|
| gptkbp:canBe |
Experimental data
Observational data |
| gptkbp:contrastsWith |
Correlation-based models
Undirected graphical models |
| gptkbp:enables |
Counterfactual reasoning
Intervention analysis Prediction of causal effects |
| gptkbp:formedBy |
gptkb:Judea_Pearl
|
| gptkbp:hasComponent |
Nodes
Conditional probability distributions Directed edges |
| gptkbp:relatedTo |
Directed acyclic graphs
Do-calculus Structural equation models |
| gptkbp:represents |
Random variables
Causal dependencies |
| gptkbp:requires |
Assumptions of Markov condition
Assumptions of causal sufficiency Assumptions of faithfulness |
| gptkbp:usedFor |
Causal inference
Probabilistic reasoning Representation of causal relationships |
| gptkbp:visualizes |
gptkb:Directed_acyclic_graph
|
| gptkbp:bfsParent |
gptkb:Probabilistic_Causation
|
| gptkbp:bfsLayer |
8
|
| https://www.w3.org/2000/01/rdf-schema#label |
Causal Bayesian networks
|