public interface TransitionWithSufficientStatistic extends Transition
TrainableTransition
and SamplingTransition
can be used to estimate the parameters (cf. TrainableTransition.estimateFromStatistic()
)
or to draw new parameters (cf. SamplingFromStatistic.drawParametersFromStatistic()
).TrainableTransition
,
SamplingTransition
Modifier and Type | Method and Description |
---|---|
void |
addToStatistic(int layer,
int index,
int childIdx,
double weight,
Sequence sequence,
int sequencePosition)
This method allows to add a certain
weight to the sufficient statistic of a specific transition. |
double |
getLogGammaScoreFromStatistic()
This method calculates a score for the current statistics, which is independent from the current parameters
In general the gamma-score is a product of gamma-functions parameterized with the current statistics
|
void |
joinStatistics(Transition... transitions)
This method joins the statistics of different instances and sets this joined statistic as statistic of each instance.
|
void |
resetStatistic()
This method reset the internal sufficient statistics that can be used for estimating the parameters.
|
clone, fillTransitionInformation, getChildIdx, getGraphizNetworkRepresentation, getLastContextState, getLogPriorTerm, getLogScoreFor, getMaximalInDegree, getMaximalMarkovOrder, getMaximalNumberOfChildren, getNumberOfChildren, getNumberOfIndexes, getNumberOfStates, hasAnySelfTransitions, initializeRandomly, isAbsoring, setParameters, toString
void resetStatistic()
void addToStatistic(int layer, int index, int childIdx, double weight, Sequence sequence, int sequencePosition)
weight
to the sufficient statistic of a specific transition.layer
- the layer of the matrixindex
- the index encoding the contextchildIdx
- the index of the childweight
- the weight added to the sufficient statisticsequence
- the sequencesequencePosition
- the position within the sequencevoid joinStatistics(Transition... transitions)
transitions
- the transitions to be joineddouble getLogGammaScoreFromStatistic()