edu.stanford.nlp.classify
Class SemiSupervisedLogConditionalObjectiveFunction

java.lang.Object
  extended by edu.stanford.nlp.optimization.AbstractCachingDiffFunction
      extended by 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
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc, AbstractCachingDiffFunction biasedObjFunc, LogPrior prior)
           
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction objFunc, AbstractCachingDiffFunction biasedObjFunc, LogPrior prior, double convexComboFrac)
           
 
Method Summary
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, 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


Stanford NLP Group