edu.stanford.nlp.classify
Class BiasedLogConditionalObjectiveFunction
java.lang.Object
edu.stanford.nlp.optimization.AbstractCachingDiffFunction
edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
- All Implemented Interfaces:
- DiffFunction, Function, HasInitial
public class BiasedLogConditionalObjectiveFunction
- extends AbstractCachingDiffFunction
Maximizes the conditional likelihood with a given prior.
- Author:
- Jenny Finkel
Constructor Summary |
BiasedLogConditionalObjectiveFunction(GeneralDataset dataset,
double[][] confusionMatrix)
|
BiasedLogConditionalObjectiveFunction(GeneralDataset dataset,
double[][] confusionMatrix,
LogPrior prior)
|
BiasedLogConditionalObjectiveFunction(int numFeatures,
int numClasses,
int[][] data,
int[] labels,
double[][] confusionMatrix)
|
BiasedLogConditionalObjectiveFunction(int numFeatures,
int numClasses,
int[][] data,
int[] labels,
double[][] confusionMatrix,
LogPrior prior)
|
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 |
protected int |
indexOf(int f,
int c)
|
void |
setPrior(LogPrior prior)
|
double[][] |
to2D(double[] x)
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
prior
protected LogPrior prior
numFeatures
protected int numFeatures
numClasses
protected int numClasses
data
protected int[][] data
labels
protected int[] labels
BiasedLogConditionalObjectiveFunction
public BiasedLogConditionalObjectiveFunction(GeneralDataset dataset,
double[][] confusionMatrix)
BiasedLogConditionalObjectiveFunction
public BiasedLogConditionalObjectiveFunction(GeneralDataset dataset,
double[][] confusionMatrix,
LogPrior prior)
BiasedLogConditionalObjectiveFunction
public BiasedLogConditionalObjectiveFunction(int numFeatures,
int numClasses,
int[][] data,
int[] labels,
double[][] confusionMatrix)
BiasedLogConditionalObjectiveFunction
public BiasedLogConditionalObjectiveFunction(int numFeatures,
int numClasses,
int[][] data,
int[] labels,
double[][] confusionMatrix,
LogPrior prior)
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
- Specified by:
domainDimension
in interface Function
- Specified by:
domainDimension
in class AbstractCachingDiffFunction
- Returns:
- the number of domain dimensions
indexOf
protected int indexOf(int f,
int c)
to2D
public double[][] to2D(double[] x)
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
Stanford NLP Group