CRF-package |
CRF - Conditional Random Fields |
Chain |
Chain CRF example |
clamp.crf |
Make clamped CRF |
clamp.reset |
Reset clamped CRF |
Clique |
Clique CRF example |
CRF |
CRF - Conditional Random Fields |
crf.nll |
Calculate CRF negative log likelihood |
crf.update |
Update CRF potentials |
decode.block |
Decoding method using block iterated conditional modes algorithm |
decode.chain |
Decoding method for chain-structured graphs |
decode.conditional |
Conditional decoding method |
decode.cutset |
Decoding method for graphs with a small cutset |
decode.exact |
Decoding method for small graphs |
decode.greedy |
Decoding method using greedy algorithm |
decode.icm |
Decoding method using iterated conditional modes algorithm |
decode.ilp |
Decoding method using integer linear programming |
decode.junction |
Decoding method for low-treewidth graphs |
decode.lbp |
Decoding method using loopy belief propagation |
decode.marginal |
Decoding method using inference |
decode.rbp |
Decoding method using residual belief propagation |
decode.sample |
Decoding method using sampling |
decode.trbp |
Decoding method using tree-reweighted belief propagation |
decode.tree |
Decoding method for tree- and forest-structured graphs |
duplicate.crf |
Duplicate CRF |
get.logPotential |
Calculate the log-potential of CRF |
get.potential |
Calculate the potential of CRF |
infer.chain |
Inference method for chain-structured graphs |
infer.conditional |
Conditional inference method |
infer.cutset |
Inference method for graphs with a small cutset |
infer.exact |
Inference method for small graphs |
infer.junction |
Inference method for low-treewidth graphs |
infer.lbp |
Inference method using loopy belief propagation |
infer.rbp |
Inference method using residual belief propagation |
infer.sample |
Inference method using sampling |
infer.trbp |
Inference method using tree-reweighted belief propagation |
infer.tree |
Inference method for tree- and forest-structured graphs |
Loop |
Loop CRF example |
make.crf |
Make CRF |
make.features |
Make CRF features |
make.par |
Make CRF parameters |
mrf.nll |
Calculate MRF negative log-likelihood |
mrf.stat |
Calculate MRF sufficient statistics |
mrf.update |
Update MRF potentials |
Rain |
Rain data |
sample.chain |
Sampling method for chain-structured graphs |
sample.conditional |
Conditional sampling method |
sample.cutset |
Sampling method for graphs with a small cutset |
sample.exact |
Sampling method for small graphs |
sample.gibbs |
Sampling method using single-site Gibbs sampler |
sample.junction |
Sampling method for low-treewidth graphs |
sample.tree |
Sampling method for tree- and forest-structured graphs |
Small |
Small CRF example |
sub.crf |
Make sub CRF |
train.crf |
Train CRF model |
train.mrf |
Train MRF model |
Tree |
Tree CRF example |