edu.umass.cs.mallet.base.fst
Class CRF_PL
java.lang.Object
edu.umass.cs.mallet.base.fst.Transducer
edu.umass.cs.mallet.base.fst.CRF4
edu.umass.cs.mallet.base.fst.CRF_PL
- All Implemented Interfaces:
- java.io.Serializable
- public class CRF_PL
- extends CRF4
- implements java.io.Serializable
A CRF trained by pseudolikelihood. zt test time, the standard, globally-normalized
model as used, as in the clssical work on pseudolikelihood.
- See Also:
- Serialized Form
Method Summary |
void |
gatherTrainingSets(InstanceList training)
|
CRF4.MaximizableCRF |
getMaximizableCRF(InstanceList ilist)
|
void |
initializeTrainingFor(InstanceList training)
|
protected CRF4.State |
newState(java.lang.String name,
int index,
double initialCost,
double finalCost,
java.lang.String[] destinationNames,
java.lang.String[] labelNames,
java.lang.String[][] weightNames,
CRF4 crf)
|
void |
printInstanceLists()
|
boolean |
train(InstanceList training,
InstanceList validation,
InstanceList testing,
TransducerEvaluator eval,
int numIterations)
|
boolean |
train(InstanceList training,
InstanceList validation,
InstanceList testing,
TransducerEvaluator eval,
int numIterations,
int numIterationsPerProportion,
double[] trainingProportions)
|
boolean |
trainWithFeatureInduction(InstanceList trainingData,
InstanceList validationData,
InstanceList testingData,
TransducerEvaluator eval,
int numIterations,
int numIterationsBetweenFeatureInductions,
int numFeatureInductions,
int numFeaturesPerFeatureInduction,
double trueLabelProbThreshold,
boolean clusteredFeatureInduction,
double[] trainingProportions,
java.lang.String gainName)
|
Methods inherited from class edu.umass.cs.mallet.base.fst.CRF4 |
addFullyConnectedStates, addFullyConnectedStatesForBiLabels, addFullyConnectedStatesForLabels, addFullyConnectedStatesForThreeQuarterLabels, addFullyConnectedStatesForTriLabels, addOrderNStates, addSelfTransitioningStateForAllLabels, addStartState, addStartState, addState, addState, addState, addState, addStatesForBiLabelsConnectedAsIn, addStatesForHalfLabelsConnectedAsIn, addStatesForLabelsConnectedAsIn, addStatesForThreeQuarterLabelsConnectedAsIn, estimate, evaluate, freezeWeights, freezeWeights, getDefaultWeights, getGaussianPriorVariance, getInputAlphabet, getOutputAlphabet, getParameter, getParametersAbsNorm, getState, getState, getTransductionType, getUseHyperbolicPriorSharpness, getUseHyperbolicPriorSlope, getUseSparseWeights, getWeights, getWeights, getWeights, getWeightsIndex, getWeightsName, initialStateIterator, isTrainable, numStates, predict, print, print, reset, setAsStartState, setDefaultWeight, setDefaultWeights, setFeatureSelection, setGaussianPriorVariance, setHyperbolicPriorSharpness, setHyperbolicPriorSlope, setParameter, setTrainable, setTransductionType, setUseHyperbolicPrior, setUseSomeUnsupportedTrick, setUseSparseWeights, setWeights, setWeights, setWeights, setWeightsDimensionAsIn, setWeightsDimensionDensely, train, train, train, trainWithFeatureInduction, transduce, transduce, unfreezeWeights, viterbiPath, write |
Methods inherited from class edu.umass.cs.mallet.base.fst.Transducer |
averageTokenAccuracy, averageTokenAccuracy, canIterateAllTransitions, forwardBackward, forwardBackward, forwardBackward, forwardBackward, forwardBackward, forwardBackward, forwardBackward, forwardBackward, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, forwardBackwardBeam, generatePath, getBeamWidth, getInputPipe, getNstatesExpl, getOutputPipe, getViterbiLattice, incIter, isGenerative, pipe, setBeamWidth, setCurIter, setKLeps, setRmin, setUseForwardBackwardBeam, stateIndexOfString, sumNegLogProb, viterbiPath_NBest, viterbiPath_NBest, viterbiPath, viterbiPath, viterbiPath, viterbiPathBeam, viterbiPathBeam, viterbiPathBeam, viterbiPathBeamB, viterbiPathBeamB, viterbiPathBeamB, viterbiPathBeamB, viterbiPathBeamFB, viterbiPathBeamFB, viterbiPathBeamFB, viterbiPathBeamFB, viterbiPathBeamKL, viterbiPathBeamKL, viterbiPathBeamKL |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
dumpProbabilities
public boolean dumpProbabilities
CRF_PL
public CRF_PL(CRF4 crf)
newState
protected CRF4.State newState(java.lang.String name,
int index,
double initialCost,
double finalCost,
java.lang.String[] destinationNames,
java.lang.String[] labelNames,
java.lang.String[][] weightNames,
CRF4 crf)
- Overrides:
newState
in class CRF4
train
public boolean train(InstanceList training,
InstanceList validation,
InstanceList testing,
TransducerEvaluator eval,
int numIterations)
- Overrides:
train
in class CRF4
initializeTrainingFor
public void initializeTrainingFor(InstanceList training)
gatherTrainingSets
public void gatherTrainingSets(InstanceList training)
train
public boolean train(InstanceList training,
InstanceList validation,
InstanceList testing,
TransducerEvaluator eval,
int numIterations,
int numIterationsPerProportion,
double[] trainingProportions)
- Overrides:
train
in class CRF4
trainWithFeatureInduction
public boolean trainWithFeatureInduction(InstanceList trainingData,
InstanceList validationData,
InstanceList testingData,
TransducerEvaluator eval,
int numIterations,
int numIterationsBetweenFeatureInductions,
int numFeatureInductions,
int numFeaturesPerFeatureInduction,
double trueLabelProbThreshold,
boolean clusteredFeatureInduction,
double[] trainingProportions,
java.lang.String gainName)
- Overrides:
trainWithFeatureInduction
in class CRF4
getMaximizableCRF
public CRF4.MaximizableCRF getMaximizableCRF(InstanceList ilist)
- Overrides:
getMaximizableCRF
in class CRF4
printInstanceLists
public void printInstanceLists()