See: Description
Interface | Description |
---|---|
DifferentiableState |
This interface declares a method that allows to evaluate the gradient which is essential for numerical optimization.
|
SamplingState | |
State |
This interface declares the methods of any state used in a hidden Markov model.
|
TrainableState |
This class implements method that allows to fill a statistic, which is used to estimate the parameters of a state during, for instance, the Baum-Welch training.
|
Class | Description |
---|---|
SimpleDifferentiableState | |
SimpleSamplingState |
This class implements a state that can be used for a HMM that obtains its parameters from sampling.
|
SimpleState |
State
,
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions