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Provide trainers which estimate parameters based on training sequences.
These should be used to 'train' a Markov Model prior to actually using it to decode state paths. When supplied training sequences and a model to work from, these classes will estimate parameters of the model.
This aims to estimate two parameters:
 a_{kl}  the number of times there is a transition from k to l in the training data.
 e_{k}(b)  the number of emissions of the state b from the letter k in the training data.


TrainingSequence Hold a training sequence with emissions and optionally, a state path. 

AbstractTrainer Provide generic functionality needed in all trainers. 

BaumWelchTrainer Trainer that uses the BaumWelch algorithm to estimate parameters. 

KnownStateTrainer Estimate probabilities with known state sequences. 


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