train.mrf: Train MRF model

In CRF: Conditional Random Fields

Description

Train the MRF model to estimate the parameters

Usage

train.mrf(
  crf,
  instances,
  nll = mrf.nll,
  infer.method = infer.chain,
  ...,
  trace = 0
)

Arguments

crf	The CRF
instances	The training data matrix of CRF model
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 trains the Markov Random Fields (MRF) model, which is a simple variant of CRF model.

In the training data matrix instances, each row is an instance and each column corresponds a node in CRF.

Value

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

See Also

mrf.update, mrf.stat, mrf.nll, make.crf

CRF documentation built on Dec. 1, 2019, 3:02 a.m.