Calculate the negative log likelihood of CRF model
crf.nll(
par,
crf,
instances,
node.fea = NULL,
edge.fea = NULL,
node.ext = NULL,
edge.ext = NULL,
infer.method = infer.chain,
...
)
The parameter vector of CRF
The CRF
The training data matrix of CRF model
The list of node features
The list of edge features
The list of extended information of node features
The list of extended information of edge features
The inference method used to compute the likelihood
Extra parameters need by the inference method
This function will return the value of CRF negative log-likelihood.
This function calculates the negative log likelihood of CRF model as well as the gradient. This function is intended to be called by optimization algorithm in training process.
In the training data matrix instances
, each row is an instance and
each column corresponds a node in CRF.
The variables node.fea
, edge.fea
, node.ext
, edge.ext
are lists of length equal to the number of instances, and their elements are
defined as in crf.update
respectively.