Properties (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Model
|
| gptkbp:allows |
Inference
Decision making |
| gptkbp:appliesTo |
Causal reasoning
|
| gptkbp:can_be |
Markov Chain Monte Carlo
Maximum likelihood estimation Bayesian inference |
| gptkbp:composedOf |
Edges
Nodes |
| gptkbp:developedBy |
Judea Pearl
|
| gptkbp:hasRelatedPatent |
Bioinformatics
Finance Natural language processing Robotics |
| gptkbp:hasResearchInterest |
Data
|
| https://www.w3.org/2000/01/rdf-schema#label |
Bayesian Networks
|
| gptkbp:isAccessibleBy |
Statistical methods
Expert knowledge |
| gptkbp:isCharacterizedBy |
Marginalization
D-separation Parameter learning Structure learning Bayes'_theorem |
| gptkbp:isEvaluatedBy |
gptkb:AIC
gptkb:BIC Cross-validation Likelihood ratio test |
| gptkbp:isFacilitatedBy |
Uncertainty
|
| gptkbp:isLocatedIn |
Programming languages
Software tools |
| gptkbp:isPopularIn |
Data science
Artificial intelligence research Machine learning research Statistics research |
| gptkbp:isRelatedTo |
Graph theory
Hidden Markov models Decision trees |
| gptkbp:isUsedFor |
gptkb:Dynamic_Bayesian_networks
Classification Diagnosis Prediction Directed acyclic graph Temporal Bayesian networks |
| gptkbp:isUsedIn |
Risk assessment
Medical diagnosis Fraud detection Recommendation systems |
| gptkbp:isUtilizedFor |
Parameter estimation
Model selection Data sparsity Complexity of inference |
| gptkbp:mayHave |
Joint probability distribution
|
| gptkbp:represents |
Conditional dependencies
|
| gptkbp:usedIn |
Artificial intelligence
Machine learning Statistics |