CRFNonLinearLogConditionalObjectiveFunction (Stanford JavaNLP API)

java.lang.Object
- edu.stanford.nlp.optimization.AbstractCachingDiffFunction
- - edu.stanford.nlp.ie.crf.CRFNonLinearLogConditionalObjectiveFunction

All Implemented Interfaces:: HasCliquePotentialFunction, DiffFunction, Function, HasFeatureGrouping, HasInitial, HasRegularizerParamRange

public class CRFNonLinearLogConditionalObjectiveFunction
extends AbstractCachingDiffFunction
implements HasCliquePotentialFunction, HasFeatureGrouping, HasRegularizerParamRange

Author:: Mengqiu Wang

Field Summary

Fields
Modifier and Type	Field and Description
`static boolean`	`DEBUG`
`protected double`	`epsilon`
`boolean`	`gradientsOnly`
`static int`	`HUBER_PRIOR`
`static int`	`L1_PRIOR`
`static int`	`NO_PRIOR`
`protected int`	`prior`
`static int`	`QUADRATIC_PRIOR`
`static int`	`QUARTIC_PRIOR`
`protected double`	`sigma`
`static boolean`	`VERBOSE`

Fields inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
derivative, value

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`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[][]`	`empty2D()`
`double[][]`	`emptyFull2D()`
`CliquePotentialFunction`	`getCliquePotentialFunction(double[] x)`
`int[][]`	`getFeatureGrouping()`
`static int`	`getPriorType(java.lang.String priorTypeStr)`
`java.util.Set<java.lang.Integer>`	`getRegularizerParamRange(double[] x)`
`double[]`	`initial()` Returns the intitial point in the domain (but not necessarily a feasible one).
`Triple<double[][],double[][],double[][]>`	`separateWeights(double[] x)`
`double[][]`	`to2D(double[] linearWeights)`

Methods inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
clearCache, copy, derivativeAt, ensure, getDerivative, gradientCheck, gradientCheck, lastValue, randomInitial, valueAt

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - 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
  - L1_PRIOR
```
public static final int L1_PRIOR
```
    See Also:
    
    Constant Field Values
  - prior
```
protected int prior
```
  - sigma
```
protected double sigma
```
  - epsilon
```
protected double epsilon
```
  - VERBOSE
```
public static boolean VERBOSE
```
  - DEBUG
```
public static boolean DEBUG
```
  - gradientsOnly
```
public boolean gradientsOnly
```
- Method Detail
  - 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
    
    Specified by:
    
    domainDimension in interface Function
    
    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 Triple<double[][],double[][],double[][]> separateWeights(double[] x)
```
  - getCliquePotentialFunction
```
public CliquePotentialFunction getCliquePotentialFunction(double[] x)
```
    Specified by:
    
    getCliquePotentialFunction in interface HasCliquePotentialFunction
  - 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
  - getRegularizerParamRange
```
public java.util.Set<java.lang.Integer> getRegularizerParamRange(double[] x)
```
    Specified by:
    
    getRegularizerParamRange in interface HasRegularizerParamRange
  - to2D
```
public double[][] to2D(double[] linearWeights)
```
  - empty2D
```
public double[][] empty2D()
```
  - emptyFull2D
```
public double[][] emptyFull2D()
```
  - getFeatureGrouping
```
public int[][] getFeatureGrouping()
```
    Specified by:
    
    getFeatureGrouping in interface HasFeatureGrouping

Class CRFNonLinearLogConditionalObjectiveFunction

Field Summary

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

Method Summary

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

Methods inherited from class java.lang.Object

Field Detail

NO_PRIOR

QUADRATIC_PRIOR

HUBER_PRIOR

QUARTIC_PRIOR

L1_PRIOR

prior

sigma

epsilon

VERBOSE

DEBUG

gradientsOnly

Method Detail

getPriorType

domainDimension

initial

separateWeights

getCliquePotentialFunction

calculate

getRegularizerParamRange

to2D

empty2D

emptyFull2D

getFeatureGrouping