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Packages that use Transition | |
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danbikel.parser | Provides the core framework of this extensible statistical parsing engine. |
Uses of Transition in danbikel.parser |
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Fields in danbikel.parser declared as Transition | |
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Transition[] |
ProbabilityStructure.transitions
A reusable Transition array to store transitions. |
Methods in danbikel.parser that return Transition | |
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Transition |
Transition.copy()
Returns a deep copy of this Transition object. |
Transition |
Transition.copyCanonical(Map canonicalFutures,
Map canonicalHistories)
Returns a copy of this object with canonical versions of the history and future events. |
protected static Transition |
Model.getCanonical(Transition trans,
FlexibleMap canonical)
This method assumes trans already contains a canonical history and a canonical future. |
Transition |
ProbabilityStructure.getTransition(TrainerEvent trainerEvent,
int backOffLevel)
Returns the reusable transition object for the specified back-off level, with its history set to the result of calling getHistory(trainerEvent, backOffLevel) and its
future the result of getFuture(trainerEvent, backOffLevel) . |
protected Transition[] |
Model.getTransitions(Transition zeroLevelTrans,
Transition[] trans)
Inserts the Transition objects representing conditional events for
all back-off levels of this model into the specified array, with
trans[0] = zeroLevelTrans . |
Methods in danbikel.parser with parameters of type Transition | |
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protected double |
Model.estimateLogProbUsingPrecomputed(Transition transition,
int atLevel)
Estimates the log prob of the specified transition using precomputed probabilities and lambdas and Model.histBackOffMap (debugging method). |
protected static Transition |
Model.getCanonical(Transition trans,
FlexibleMap canonical)
This method assumes trans already contains a canonical history and a canonical future. |
static double[] |
AnalyzeDisns.getLogProbDisn(Model model,
int level,
Event hist,
Set futures,
double[] disn,
Transition tmpTrans)
Returns the smoothed log-probability distribution for the specified history at the specified back-off level in the specified model. |
protected Transition[] |
Model.getTransitions(Transition zeroLevelTrans,
Transition[] trans)
Inserts the Transition objects representing conditional events for
all back-off levels of this model into the specified array, with
trans[0] = zeroLevelTrans . |
protected Transition[] |
Model.getTransitions(Transition zeroLevelTrans,
Transition[] trans)
Inserts the Transition objects representing conditional events for
all back-off levels of this model into the specified array, with
trans[0] = zeroLevelTrans . |
protected void |
InterpolatedKnesserNeyModel.precomputeProbs(MapToPrimitive.Entry transEntry,
double[] lambdas,
double[] estimates,
Transition[] transitions,
Event[] histories,
int lastLevel)
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protected void |
Model.precomputeProbs(MapToPrimitive.Entry transEntry,
double[] lambdas,
double[] estimates,
Transition[] transitions,
Event[] histories,
int lastLevel)
Precomputes the probabilities and smoothing values for the Transition object contained as a key within the specified
map entry, where the value is the count of the transition. |
protected void |
InterpolatedKnesserNeyModel.precomputeProbs(TrainerEvent event,
Transition[] transitions,
Event[] histories)
Deprecated. This method is called by Model.precomputeProbs(CountsTable,Filter) , which is also deprecated. |
protected void |
Model.precomputeProbs(TrainerEvent event,
Transition[] transitions,
Event[] histories)
Deprecated. This method is called by Model.precomputeProbs(CountsTable,Filter) , which is also deprecated. |
static void |
PrintDisn.printLogProbDisn(PrintWriter writer,
ModelCollection mc,
Model model,
int level,
Event hist,
Set futures,
Transition tmpTrans)
Prints the log-probability distribution of the specified event at the specified back-off level of the specified model to the specified writer. |
boolean |
ProbabilityStructure.removeTransition(int backOffLevel,
Transition transition)
Returns true if the specified transition contains
either a history or future for which ProbabilityStructure.removeHistory(int,Event) or ProbabilityStructure.removeFuture(int,Event)
returns true , respectively. |
protected void |
InterpolatedKnesserNeyModel.storePrecomputedProbs(double[] lambdas,
double[] estimates,
Transition[] transitions,
Event[] histories,
int lastLevel)
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protected void |
Model.storePrecomputedProbs(double[] lambdas,
double[] estimates,
Transition[] transitions,
Event[] histories,
int lastLevel)
Stores the specified smoothing values (lambdas) and smoothed probability estimates in the Model.precomputedProbs and Model.smoothingParams
map arrays. |
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