| Class | Description |
|---|---|
| HiddenMarkovModel |
This is the hidden Markov model as defined by Rabiner.
|
| HmmForwardBackward |
The forward–backward algorithm is an inference algorithm for hidden Markov models
which computes the posterior marginals of all hidden state variables given a sequence of observations.
|
| HmmGamma |
γ is the probability of the system in state si,
given the model and observation sequence.
|
| HmmTrainByEM |
This implementation trains an HMM model by observations using an EM algorithm.
|
| HmmXi |
ξ is the probability of the system being in state si at time t and state sj at time t+1,
given the model and observation sequence.
|