train.crf {CRF}

Train CRF model

Description

Train the CRF model to estimate the parameters

Usage

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
)

Arguments

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

Details

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.

Value

This function will directly modify the CRF and return the same CRF.

See Also

crf.update, crf.nll, make.crf