This package is an implementation of a linear Markov chain
Conditional Random Field (CRF) model that uses boosted regression trees
for training and inference.
Train a new CRF model with the maximum number of boosting iterations
specified in the configuration given to the constructor but with the
option to stop early if the incremental improvement in Viterbi accuracy
is less than the amount specified in the configuration.