cc.mallet.grmm.learning
Class ACRF.MaximizableACRF

java.lang.Object
  cc.mallet.grmm.learning.ACRF.MaximizableACRF

All Implemented Interfaces:

Optimizable, Optimizable.ByGradientValue, java.io.Serializable

Enclosing class:

ACRF

public class ACRF.MaximizableACRF
extends java.lang.Object
implements Optimizable.ByGradientValue, java.io.Serializable

See Also:

Serialized Form

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

Field Summary

protected Inferencer	inferencer
protected java.util.BitSet	infiniteValues

Constructor Summary

protected

ACRF.MaximizableACRF(InstanceList ilist)

Method Summary

void	collectConstraints(InstanceList ilist)
protected double	computeLogLikelihood()
void	forceStale()
SparseVector[]	getConstraints(int cnum)
SparseVector[]	getExpectations(int cnum)
int	getNumParameters()
double	getParameter(int index)
void	getParameters(double[] buf)
int	getTotalNodes()
double	getValue() Returns the log probability of the training sequence labels
void	getValueGradient(double[] buf) Computes the graident of the penalized log likelihood of the ACRF, and returns it in buf[].
void	report()
void	setParameter(int index, double value)
void	setParameters(double[] params)

Methods inherited from class java.lang.Object

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

Field Detail

infiniteValues

protected java.util.BitSet infiniteValues

inferencer

protected Inferencer inferencer

Constructor Detail

ACRF.MaximizableACRF

protected ACRF.MaximizableACRF(InstanceList ilist)

Method Detail

getNumParameters

public int getNumParameters()

Specified by:

getNumParameters in interface Optimizable

getParameters

public void getParameters(double[] buf)

Specified by:

getParameters in interface Optimizable

setParameters

public void setParameters(double[] params)

Specified by:

setParameters in interface Optimizable

getExpectations

public SparseVector[] getExpectations(int cnum)

getConstraints

public SparseVector[] getConstraints(int cnum)

getParameter

public double getParameter(int index)

Specified by:

getParameter in interface Optimizable

setParameter

public void setParameter(int index,
                         double value)

Specified by:

setParameter in interface Optimizable

getValue

public double getValue()

Returns the log probability of the training sequence labels

Specified by:

getValue in interface Optimizable.ByGradientValue

computeLogLikelihood

protected double computeLogLikelihood()

getValueGradient

public void getValueGradient(double[] buf)

Computes the graident of the penalized log likelihood of the ACRF, and returns it in buf[].

Specified by:

getValueGradient in interface Optimizable.ByGradientValue

collectConstraints

public void collectConstraints(InstanceList ilist)

report

public void report()

forceStale

public void forceStale()

getTotalNodes

public int getTotalNodes()