Package cc.mallet.fst.semi_supervised

Class CRFOptimizableByGE

java.lang.Object

cc.mallet.fst.semi_supervised.CRFOptimizableByGE

All Implemented Interfaces:

Optimizable, Optimizable.ByGradientValue

public class CRFOptimizableByGE
extends java.lang.Object
implements Optimizable.ByGradientValue

Optimizable for CRF using Generalized Expectation constraints that consider either a single label or a pair of labels of a linear chain CRF. See: "Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields" Gideon Mann and Andrew McCallum ACL 2008

Author:

Gregory Druck

Nested Class Summary

Nested classes/interfaces inherited from interface cc.mallet.optimize.Optimizable

Optimizable.ByBatchGradient, Optimizable.ByCombiningBatchGradient, Optimizable.ByGISUpdate, Optimizable.ByGradient, Optimizable.ByGradientValue, Optimizable.ByHessian, Optimizable.ByValue, Optimizable.ByVotedPerceptron

Constructor Summary

Constructors

Constructor	Description
CRFOptimizableByGE(CRF crf, java.util.ArrayList<GEConstraint> constraints, InstanceList data, StateLabelMap map, int numThreads)
CRFOptimizableByGE(CRF crf, java.util.ArrayList<GEConstraint> constraints, InstanceList data, StateLabelMap map, int numThreads, double weight)

Method Summary

Modifier and Type	Method	Description
void	cacheValueAndGradient()
void	createReverseTransitionMatrices(CRF crf)	Initializes data structures for mapping between a destination state and its source states / transition indices.
int	getNumParameters()
double	getParameter(int index)
void	getParameters(double[] buffer)
double	getValue()
void	getValueGradient(double[] buffer)
void	setGaussianPriorVariance(double variance)
void	setParameter(int index, double value)
void	setParameters(double[] params)
void	shutdown()	Should be called after training is complete to shutdown all threads.

Methods inherited from class java.lang.Object

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

Constructor Detail

CRFOptimizableByGE

public CRFOptimizableByGE(CRF crf,
                          java.util.ArrayList<GEConstraint> constraints,
                          InstanceList data,
                          StateLabelMap map,
                          int numThreads)

Parameters:

crf - CRF

constraints - List of GEConstraints

data - Unlabeled data.

map - Map between states and labels.

numThreads - Number of threads to use for training (DEFAULT=1)

CRFOptimizableByGE

public CRFOptimizableByGE(CRF crf,
                          java.util.ArrayList<GEConstraint> constraints,
                          InstanceList data,
                          StateLabelMap map,
                          int numThreads,
                          double weight)

Method Detail

createReverseTransitionMatrices

public void createReverseTransitionMatrices(CRF crf)

Initializes data structures for mapping between a destination state and its source states / transition indices.

Parameters:

crf - CRF

getNumParameters

public int getNumParameters()

Specified by:

getNumParameters in interface Optimizable

getParameters

public void getParameters(double[] buffer)

Specified by:

getParameters in interface Optimizable

getParameter

public double getParameter(int index)

Specified by:

getParameter in interface Optimizable

setParameters

public void setParameters(double[] params)

Specified by:

setParameters in interface Optimizable

setParameter

public void setParameter(int index,
                         double value)

Specified by:

setParameter in interface Optimizable

cacheValueAndGradient

public void cacheValueAndGradient()

setGaussianPriorVariance

public void setGaussianPriorVariance(double variance)

getValueGradient

public void getValueGradient(double[] buffer)

Specified by:

getValueGradient in interface Optimizable.ByGradientValue

getValue

public double getValue()

Specified by:

getValue in interface Optimizable.ByGradientValue

shutdown

public void shutdown()

Should be called after training is complete to shutdown all threads.