edu.stanford.nlp.ie.crf
Class CRFNonLinearSecondOrderLogConditionalObjectiveFunction
java.lang.Object
edu.stanford.nlp.optimization.AbstractCachingDiffFunction
edu.stanford.nlp.ie.crf.CRFNonLinearSecondOrderLogConditionalObjectiveFunction
- All Implemented Interfaces:
- DiffFunction, Function, HasInitial
public class CRFNonLinearSecondOrderLogConditionalObjectiveFunction
- extends AbstractCachingDiffFunction
- Author:
- Mengqiu Wang
Method Summary |
void |
calculate(double[] x)
Calculates both value and partial derivatives at the point x, and save them internally. |
int |
domainDimension()
Returns the number of dimensions in the function's domain |
double[][] |
emptyFull2D()
|
static int |
getPriorType(java.lang.String priorTypeStr)
|
double[] |
initial()
Returns the intitial point in the domain (but not necessarily a feasible one). |
Quadruple<double[][],double[][],double[][],double[][]> |
separateWeights(double[] x)
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
NO_PRIOR
public static final int NO_PRIOR
- See Also:
- Constant Field Values
QUADRATIC_PRIOR
public static final int QUADRATIC_PRIOR
- See Also:
- Constant Field Values
HUBER_PRIOR
public static final int HUBER_PRIOR
- See Also:
- Constant Field Values
QUARTIC_PRIOR
public static final int QUARTIC_PRIOR
- See Also:
- Constant Field Values
prior
protected int prior
sigma
protected double sigma
epsilon
protected double epsilon
VERBOSE
public static boolean VERBOSE
getPriorType
public static int getPriorType(java.lang.String priorTypeStr)
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
initial
public double[] initial()
- Description copied from interface:
HasInitial
- Returns the intitial point in the domain (but not necessarily a feasible one).
- Specified by:
initial
in interface HasInitial
- Overrides:
initial
in class AbstractCachingDiffFunction
- Returns:
- a domain point
separateWeights
public Quadruple<double[][],double[][],double[][],double[][]> separateWeights(double[] x)
calculate
public void calculate(double[] x)
- Calculates both value and partial derivatives at the point x, and save them internally.
- Specified by:
calculate
in class AbstractCachingDiffFunction
- Parameters:
x
- The point at which to calculate the function
emptyFull2D
public double[][] emptyFull2D()
Stanford NLP Group