gptkbp:instanceOf
|
probabilistic graphical model
|
gptkbp:alsoKnownAs
|
gptkb:Bayesian_networks
|
gptkbp:appliesTo
|
gptkb:artificial_intelligence
bioinformatics
diagnosis
decision support systems
|
gptkbp:assumes
|
conditional independence
local Markov property
|
gptkbp:canBe
|
learned from data
specified by experts
|
gptkbp:consistsOf
|
nodes
directed edges
|
gptkbp:edgesRepresent
|
conditional dependencies
|
https://www.w3.org/2000/01/rdf-schema#label
|
Bayes nets
|
gptkbp:inferenceMethod
|
gptkb:Markov_Chain_Monte_Carlo
belief propagation
variable elimination
|
gptkbp:introduced
|
gptkb:Judea_Pearl
|
gptkbp:introducedIn
|
1980s
|
gptkbp:mathematicalFoundation
|
gptkb:probability_theory
graph theory
|
gptkbp:nodesRepresent
|
random variables
|
gptkbp:relatedTo
|
gptkb:hidden_Markov_models
gptkb:Markov_networks
decision trees
causal inference
belief networks
|
gptkbp:represents
|
conditional dependencies
independencies
|
gptkbp:software
|
gptkb:GeNIe
gptkb:Netica
gptkb:bnlearn
gptkb:pgmpy
|
gptkbp:structure
|
gptkb:directed_acyclic_graph
|
gptkbp:usedFor
|
gptkb:machine_learning
probabilistic inference
causal modeling
|
gptkbp:usedIn
|
computer vision
ecology
epidemiology
finance
genetics
natural language processing
robotics
speech recognition
risk analysis
diagnosis
fraud detection
recommender systems
|
gptkbp:bfsParent
|
gptkb:Bayesian_networks
|
gptkbp:bfsLayer
|
6
|