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Packages that use Transition | |
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de.jstacs.sequenceScores.statisticalModels.trainable.hmm | The package provides all interfaces and classes for a hidden Markov model (HMM). |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions | The package provides all interfaces and classes for transitions used in hidden Markov models. |
Uses of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm |
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Fields in de.jstacs.sequenceScores.statisticalModels.trainable.hmm declared as Transition | |
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protected Transition |
AbstractHMM.transition
The transitions between all (hidden) states of the HMM. |
Uses of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions |
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Subinterfaces of Transition in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions | |
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interface |
DifferentiableTransition
This class declares methods that allow for optimizing the parameters numerically using the Optimizer . |
interface |
SamplingTransition
This interface declares all method used during a sampling. |
interface |
TrainableAndDifferentiableTransition
This interface unifies the interfaces TrainableTransition and DifferentiableTransition . |
interface |
TrainableTransition
This class declares methods that allow for estimating the parameters from a sufficient statistic, as for instance done in the (modified) Baum-Welch algorithm, viterbi training, or Gibbs sampling. |
interface |
TransitionWithSufficientStatistic
This interface defines method for reseting and filling an internal sufficient statistic. |
Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions that implement Transition | |
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class |
BasicHigherOrderTransition
This class implements the basic transition that allows to be trained using the viterbi or the Baum-Welch algorithm. |
class |
HigherOrderTransition
This class can be used in any AbstractHMM allowing to use gradient based or sampling training algorithm. |
Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions that return Transition | |
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Transition |
Transition.clone()
This method returns a deep clone of the current instance. |
Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions with parameters of type Transition | |
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void |
TransitionWithSufficientStatistic.joinStatistics(Transition... transitions)
This method joins the statistics of different instances and sets this joined statistic as statistic of each instance. |
void |
BasicHigherOrderTransition.joinStatistics(Transition... transitions)
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void |
Transition.setParameters(Transition t)
Set values of parameters of the instance to the value of the parameters of the given instance. |
void |
BasicHigherOrderTransition.setParameters(Transition t)
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