edu.stanford.nlp.ie.crf
Class CRFLogConditionalObjectiveFunctionForLOP
java.lang.Object
edu.stanford.nlp.optimization.AbstractCachingDiffFunction
edu.stanford.nlp.ie.crf.CRFLogConditionalObjectiveFunctionForLOP
- All Implemented Interfaces:
- DiffFunction, Function, HasInitial
public class CRFLogConditionalObjectiveFunctionForLOP
- extends AbstractCachingDiffFunction
- Author:
- Mengqiu Wang
Field Summary |
static boolean |
VERBOSE
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
VERBOSE
public static boolean VERBOSE
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
empty2D
public double[][][] empty2D()
combineAndScaleLopWeights
public static double[] combineAndScaleLopWeights(int numLopExpert,
double[][] lopExpertWeights,
double[] lopScales)
combineAndScaleLopWeights2D
public static double[][] combineAndScaleLopWeights2D(int numLopExpert,
double[][][] lopExpertWeights2D,
double[] lopScales)
separateLopExpertWeights2D
public double[][][] separateLopExpertWeights2D(double[] learnedParams)
separateLopExpertWeights
public double[][] separateLopExpertWeights(double[] learnedParams)
separateLopScales
public double[] separateLopScales(double[] learnedParams)
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
Stanford NLP Group