Package edu.stanford.nlp.classify

Class SemiSupervisedLogConditionalObjectiveFunction

java.lang.Object

edu.stanford.nlp.optimization.AbstractCachingDiffFunction

edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction

All Implemented Interfaces:

DiffFunction, Function, HasInitial

public class SemiSupervisedLogConditionalObjectiveFunction
extends AbstractCachingDiffFunction

Maximizes the conditional likelihood with a given prior.

Author:

Jenny Finkel, Sarah Spikes (Templatization), Ramesh Nallapati (Made the function more general to support other AbstractCachingDiffFunctions involving the summation of two objective functions)

Field Summary

Fields inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction

derivative, value

Constructor Summary

Constructors

Constructor	Description
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc, AbstractCachingDiffFunction biasedObjFunc, LogPrior prior)
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc, AbstractCachingDiffFunction biasedObjFunc, LogPrior prior, double convexComboFrac)

Method Summary

Modifier and Type	Method	Description
protected void	calculate(double[] x)	Calculate the value at x and the derivative and save them in the respective fields.
int	domainDimension()	Returns the number of dimensions in the function's domain
void	setPrior(LogPrior prior)

Methods inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction

clearCache, copy, derivativeAt, ensure, getDerivative, gradientCheck, gradientCheck, initial, lastValue, randomInitial, valueAt

Methods inherited from class java.lang.Object

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

Constructor Detail

SemiSupervisedLogConditionalObjectiveFunction

public SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc,
                                                     AbstractCachingDiffFunction biasedObjFunc,
                                                     LogPrior prior,
                                                     double convexComboFrac)

SemiSupervisedLogConditionalObjectiveFunction

public SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc,
                                                     AbstractCachingDiffFunction biasedObjFunc,
                                                     LogPrior prior)

Method Detail

setPrior

public void setPrior(LogPrior prior)

domainDimension

public int domainDimension()

Description copied from interface: Function

Returns the number of dimensions in the function's domain

Returns:

the number of domain dimensions

calculate

protected void calculate(double[] x)

Description copied from class: AbstractCachingDiffFunction

Calculate the value at x and the derivative and save them in the respective fields.

Specified by:

calculate in class AbstractCachingDiffFunction

Parameters:

x - The point at which to calculate the function