cc.mallet.fst.semi_supervised.pr.constraints
Interface PRConstraint

All Known Implementing Classes:

OneLabelL2IndPRConstraints, OneLabelL2PRConstraints

public interface PRConstraint

Interface for PR constraint that considers either one or two states.

Author:

Gregory Druck

Method Summary

void	addExpectations(double[] expectations)
PRConstraint	copy() This is used in multi-threading.
double	getAuxiliaryValueContribution(double[] parameters)
double	getCompleteValueContribution(double[] parameters)
void	getExpectations(double[] expectations)
void	getGradient(double[] parameters, double[] gradient)
double	getScore(FeatureVector input, int inputPosition, int srcIndex, int destIndex, double[] parameters)
void	incrementExpectations(FeatureVector input, int inputPosition, int srcIndex, int destIndex, double prob)
int	numDimensions()
void	preProcess(FeatureVector input) Gives the constraint the option to do some caching using only the FeatureVector.
java.util.BitSet	preProcess(InstanceList data)
void	setStateLabelMap(StateLabelMap map) Sets that map between the state indices and label indices.
void	zeroExpectations() Zero expectation values.

Method Detail

numDimensions

int numDimensions()

getScore

double getScore(FeatureVector input,
                int inputPosition,
                int srcIndex,
                int destIndex,
                double[] parameters)

incrementExpectations

void incrementExpectations(FeatureVector input,
                           int inputPosition,
                           int srcIndex,
                           int destIndex,
                           double prob)

getAuxiliaryValueContribution

double getAuxiliaryValueContribution(double[] parameters)

getCompleteValueContribution

double getCompleteValueContribution(double[] parameters)

getGradient

void getGradient(double[] parameters,
                 double[] gradient)

setStateLabelMap

void setStateLabelMap(StateLabelMap map)

Sets that map between the state indices and label indices.

Parameters:

map - StateLabelMap

zeroExpectations

void zeroExpectations()

Zero expectation values. Called before re-computing gradient.

preProcess

java.util.BitSet preProcess(InstanceList data)

Parameters:

data - Unlabeled data

Returns:

Returns a bitset of the size of the data, with the bit set if a constraint feature fires in that instance.

preProcess

void preProcess(FeatureVector input)

Gives the constraint the option to do some caching using only the FeatureVector. For example, the constrained input features could be cached.

Parameters:

input - FeatureVector input

copy

PRConstraint copy()

This is used in multi-threading.

Returns:

A copy of the GEConstraint.

getExpectations

void getExpectations(double[] expectations)

addExpectations

void addExpectations(double[] expectations)