cc.mallet.fst

Class CRFTrainerByStochasticGradient

java.lang.Object

cc.mallet.fst.TransducerTrainer

cc.mallet.fst.TransducerTrainer.ByIncrements

cc.mallet.fst.TransducerTrainer.ByInstanceIncrements

cc.mallet.fst.CRFTrainerByStochasticGradient

public class CRFTrainerByStochasticGradient
extends TransducerTrainer.ByInstanceIncrements

Trains CRF by stochastic gradient. Most effective on large training sets.

Nested Class Summary

Nested classes/interfaces inherited from class cc.mallet.fst.TransducerTrainer

TransducerTrainer.ByIncrements, TransducerTrainer.ByInstanceIncrements, TransducerTrainer.ByOptimization

Constructor Summary

Constructors

Constructor and Description
CRFTrainerByStochasticGradient(CRF crf, double learningRate)
CRFTrainerByStochasticGradient(CRF crf, InstanceList trainingSample)

Method Summary

Modifier and Type	Method and Description
int	getIteration()
double	getLearningRate()
Transducer	getTransducer()
boolean	isFinishedTraining()
void	setLearningRate(double r)
void	setLearningRateByLikelihood(InstanceList trainingSample) Automatically sets the learning rate to one that would be good
boolean	train(InstanceList trainingSet, int numIterations) Train the transducer associated with this TransducerTrainer.
boolean	train(InstanceList trainingSet, int numIterations, int numIterationsBetweenEvaluation)
boolean	trainIncremental(Instance trainingInstance)
boolean	trainIncremental(InstanceList trainingSet)
double	trainIncrementalLikelihood(Instance trainingInstance) Adjust the parameters by default learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.
double	trainIncrementalLikelihood(Instance trainingInstance, double rate) Adjust the parameters by learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.

Methods inherited from class cc.mallet.fst.TransducerTrainer

addEvaluator, addEvaluators, removeEvaluator, train

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CRFTrainerByStochasticGradient

public CRFTrainerByStochasticGradient(CRF crf,
                                      InstanceList trainingSample)

CRFTrainerByStochasticGradient

public CRFTrainerByStochasticGradient(CRF crf,
                                      double learningRate)

Method Detail

getIteration

public int getIteration()

Specified by:

getIteration in class TransducerTrainer

getTransducer

public Transducer getTransducer()

Specified by:

getTransducer in class TransducerTrainer

isFinishedTraining

public boolean isFinishedTraining()

Specified by:

isFinishedTraining in class TransducerTrainer

setLearningRateByLikelihood

public void setLearningRateByLikelihood(InstanceList trainingSample)

Automatically sets the learning rate to one that would be good

setLearningRate

public void setLearningRate(double r)

getLearningRate

public double getLearningRate()

train

public boolean train(InstanceList trainingSet,
                     int numIterations)

Description copied from class: TransducerTrainer

Train the transducer associated with this TransducerTrainer. You should be able to call this method with different trainingSet objects. Whether this causes the TransducerTrainer to combine both trainingSets or to view the second as a new alternative is at the discretion of the particular TransducerTrainer subclass involved.

Specified by:

train in class TransducerTrainer

train

public boolean train(InstanceList trainingSet,
                     int numIterations,
                     int numIterationsBetweenEvaluation)

trainIncremental

public boolean trainIncremental(InstanceList trainingSet)

Specified by:

trainIncremental in class TransducerTrainer.ByIncrements

trainIncremental

public boolean trainIncremental(Instance trainingInstance)

Specified by:

trainIncremental in class TransducerTrainer.ByInstanceIncrements

trainIncrementalLikelihood

public double trainIncrementalLikelihood(Instance trainingInstance)

Adjust the parameters by default learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.

trainIncrementalLikelihood

public double trainIncrementalLikelihood(Instance trainingInstance,
                                         double rate)

Adjust the parameters by learning rate according to the gradient of this single Instance, and return the true label sequence likelihood.