Conditional Random Fields
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘CRF’ version 0.4-3
Help Pages
| 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 |