cc.mallet.classify
Class MaxEntOptimizableByGE
java.lang.Object
   cc.mallet.classify.MaxEntOptimizableByGE
cc.mallet.classify.MaxEntOptimizableByGE
- All Implemented Interfaces: 
- Optimizable, Optimizable.ByGradientValue
- public class MaxEntOptimizableByGE 
- extends java.lang.Object- implements Optimizable.ByGradientValue
- Author:
- gdruck
 
 
 
 
 
| Methods inherited from class java.lang.Object | 
| clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait | 
 
cacheStale
protected boolean cacheStale
defaultFeatureIndex
protected int defaultFeatureIndex
temperature
protected double temperature
objWeight
protected double objWeight
cachedValue
protected double cachedValue
gaussianPriorVariance
protected double gaussianPriorVariance
cachedGradient
protected double[] cachedGradient
parameters
protected double[] parameters
trainingList
protected InstanceList trainingList
classifier
protected MaxEnt classifier
constraints
protected java.util.ArrayList<MaxEntGEConstraint> constraints
MaxEntOptimizableByGE
public MaxEntOptimizableByGE(InstanceList trainingList,
                             java.util.ArrayList<MaxEntGEConstraint> constraints,
                             MaxEnt initClassifier)
- Parameters:
- trainingList- List with unlabeled training instances.
- constraints- Feature expectation constraints.
- initClassifier- Initial classifier.
setGaussianPriorVariance
public void setGaussianPriorVariance(double variance)
- Sets the variance for Gaussian prior or
 equivalently the inverse of the weight 
 of the L2 regularization term.
 
- 
 
- 
- Parameters:
- variance- Gaussian prior variance.
 
setTemperature
public void setTemperature(double temp)
- Model probabilities are raised to the power 1/temperature and 
 renormalized. As the temperature decreases, model probabilities 
 approach 1 for the maximum probability class, and 0 for other classes. 
 
 DEFAULT: 1
 
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- 
- Parameters:
- temp- Temperature.
 
setWeight
public void setWeight(double weight)
- The weight of GE term in the objective function.
 
- 
 
- 
- Parameters:
- weight- GE term weight.
 
getClassifier
public MaxEnt getClassifier()
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getValue
public double getValue()
- 
- Specified by:
- getValuein interface- Optimizable.ByGradientValue
 
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getRegularization
protected double getRegularization()
- 
 
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getValueGradient
public void getValueGradient(double[] buffer)
- 
- Specified by:
- getValueGradientin interface- Optimizable.ByGradientValue
 
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getNumParameters
public int getNumParameters()
- 
- Specified by:
- getNumParametersin interface- Optimizable
 
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getParameter
public double getParameter(int index)
- 
- Specified by:
- getParameterin interface- Optimizable
 
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getParameters
public void getParameters(double[] buffer)
- 
- Specified by:
- getParametersin interface- Optimizable
 
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setParameter
public void setParameter(int index,
                         double value)
- 
- Specified by:
- setParameterin interface- Optimizable
 
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setParameters
public void setParameters(double[] params)
- 
- Specified by:
- setParametersin interface- Optimizable
 
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