sampling hidden models
learn bounded tree-width probabilistic models with hidden variables via k-tree sampling
go get -u github.com/britojr/kbn...
go install github.com/britojr/kbn...
go test github.com/britojr/kbn... -cover
kbn --help
Usage: kbn <command> [options]
Commands:
struct sample bounded tree-width structure
param parameter learning using expectation-maximization
marginals compute marginal distribution for each variable in the model
To see details of each command:
kbn <command> --help
# move to examples directory
cd examples/
# sample a structure with tree-width 4 and 10 latent variables
kbn struct -d example.csv -cs example-struct.ct0 -k 4 -h 10
# learn parameters
kbn param -dist rand -mode indep -cl example-struct.ct0 -cs example-struct.ctp -d example.csv
# compute marginals
kbn marginals -c example-struct.ctp -m example.mar