edu.umass.cs.mallet.base.fst
Class CRF_PL

java.lang.Object
  extended byedu.umass.cs.mallet.base.fst.Transducer
      extended byedu.umass.cs.mallet.base.fst.CRF4
          extended byedu.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

Nested Class Summary
 class CRF_PL.MaximizableCRF_PL
           
static class CRF_PL.State
           
protected  class CRF_PL.TransitionIterator
           
 
Nested classes inherited from class edu.umass.cs.mallet.base.fst.CRF4
CRF4.MaximizableCRF
 
Nested classes inherited from class edu.umass.cs.mallet.base.fst.Transducer
Transducer.BeamLattice, Transducer.Lattice, Transducer.ViterbiLattice, Transducer.ViterbiPath, Transducer.ViterbiPath_NBest, Transducer.ViterbiPathBeam, Transducer.ViterbiPathBeamB, Transducer.ViterbiPathBeamFB, Transducer.ViterbiPathBeamKL
 
Field Summary
 boolean dumpProbabilities
           
 
Fields inherited from class edu.umass.cs.mallet.base.fst.CRF4
printGradient, someTrainingDone, VITERBI, VITERBI_BBEAM, VITERBI_FBBEAM, VITERBI_FBEAM, VITERBI_FBEAMKL
 
Fields inherited from class edu.umass.cs.mallet.base.fst.Transducer
INFINITE_COST, inputPipe, outputPipe, ZERO_COST
 
Constructor Summary
CRF_PL(CRF4 crf)
           
 
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
 

Field Detail

dumpProbabilities

public boolean dumpProbabilities
Constructor Detail

CRF_PL

public CRF_PL(CRF4 crf)
Method Detail

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()