R: Conditional Random Fields

# Conditional Random Fields

## Documentation for package ‘CRF’ version 0.4-3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## 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