Estimate probabilities with known state sequences.
This should be used for direct estimation of emission and transition
probabilities when both the state path and emission sequence are known
for the training examples.
Method Summary |
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__init__(self,
markov_model)
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train (self,
training_seqs)
Estimate the Markov Model parameters with known state paths. |
Inherited from AbstractTrainer |
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estimate_params (self,
transition_counts,
emission_counts)
Get a maximum likelihood estimation of transition and emmission. |
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log_likelihood (self,
probabilities)
Calculate the log likelihood of the training seqs. |
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ml_estimator (self,
counts)
Calculate the maximum likelihood estimator. |