Class AbstractTrainer

x.__init__(...) initializes x; see x.__class__.__doc__ for signature

Overrides: object.__init__

(inherited documentation)

Calculate the log likelihood of the training seqs.

Arguments:

o probabilities -- A list of the probabilities of each training
sequence under the current parameters, calculated using the forward
algorithm.

Get a maximum likelihood estimation of transition and emmission.

Arguments:

o transition_counts -- A dictionary with the total number of counts
of transitions between two states.

o emissions_counts -- A dictionary with the total number of counts
of emmissions of a particular emission letter by a state letter.

This then returns the maximum likelihood estimators for the
transitions and emissions, estimated by formulas 3.18 in
Durbin et al:

a_{kl} = A_{kl} / sum(A_{kl'})
e_{k}(b) = E_{k}(b) / sum(E_{k}(b'))

Returns:
Transition and emission dictionaries containing the maximum
likelihood estimators.

Calculate the maximum likelihood estimator.

This can calculate maximum likelihoods for both transitions
and emissions.

Arguments:

o counts -- A dictionary of the counts for each item.

See estimate_params for a description of the formula used for
calculation.