edu.stanford.nlp.optimization
Interface DiffFunction

All Superinterfaces:

Function

All Known Implementing Classes:

AbstractCachingDiffFunction, AbstractStochasticCachingDiffFunction, AbstractStochasticCachingDiffUpdateFunction, AdaptedGaussianPriorObjectiveFunction, BiasedLogConditionalObjectiveFunction, CRFLogConditionalObjectiveFunction, CRFLogConditionalObjectiveFunctionForLOP, CRFNonLinearLogConditionalObjectiveFunction, CRFNonLinearSecondOrderLogConditionalObjectiveFunction, GeneralizedExpectationObjectiveFunction, LogConditionalObjectiveFunction, SemiSupervisedLogConditionalObjectiveFunction

public interface DiffFunction
extends Function

An interface for once-differentiable double-valued functions over double arrays. NOTE: it'd be good to have an AbstractDiffFunction that wrapped a Function with a finite-difference approximation.

Since:

1.0

Author:

Dan Klein

See Also:

Function

Method Summary

double[]

derivativeAt(double[] x) Returns the first-derivative vector at the input location.

Methods inherited from interface edu.stanford.nlp.optimization.Function

domainDimension, valueAt

Method Detail

derivativeAt

double[] derivativeAt(double[] x)

Returns the first-derivative vector at the input location.

Parameters:

x - a double[] input vector

Returns:

the vector of first partial derivatives.