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.