train.crf {CRF} | R Documentation |
Train the CRF model to estimate the parameters
train.crf(
crf,
instances,
node.fea = NULL,
edge.fea = NULL,
node.ext = NULL,
edge.ext = NULL,
nll = crf.nll,
infer.method = infer.chain,
...,
trace = 0
)
crf |
The CRF |
instances |
The training data matrix of CRF model |
node.fea |
The list of node features |
edge.fea |
The list of edge features |
node.ext |
The list of extended information of node features |
edge.ext |
The list of extended information of edge features |
nll |
The function to calculate negative log likelihood |
infer.method |
The inference method used to compute the likelihood |
... |
Extra parameters need by the inference method |
trace |
Non-negative integer to control the tracing informtion of the optimization process |
This function train the CRF model.
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.
This function will directly modify the CRF and return the same CRF.