Mutual conditional independence and its applications to model selection in Markov networks.
Niharika GaurahaSwapan K. ParuiPublished in: Ann. Math. Artif. Intell. (2020)
Keyphrases
- model selection
- markov networks
- conditional independence
- graphical models
- bayesian networks
- belief propagation
- random variables
- cross validation
- structure learning
- probabilistic graphical models
- parameter estimation
- hyperparameters
- conditional independence tests
- probabilistic model
- approximate inference
- probabilistic inference
- posterior probability
- statistical learning
- conditional random fields
- sample size
- exact inference
- probability distribution
- structured prediction
- first order logic
- chain graphs
- conditional probabilities
- mixture model
- hidden variables
- machine learning
- maximum likelihood
- gaussian process
- message passing
- document classification
- causal models
- belief networks
- variable selection
- directed acyclic graph
- bayesian inference
- inductive logic programming
- naive bayes
- markov random field
- bayes nets
- semi supervised
- feature selection