org.encog.mathutil.matrices.hessian
Class HessianFD

java.lang.Object
  org.encog.mathutil.matrices.hessian.BasicHessian
      org.encog.mathutil.matrices.hessian.HessianFD

All Implemented Interfaces:

ComputeHessian

public class HessianFD
extends BasicHessian

Calculate the Hessian matrix using the finite difference method. This is a very simple method of calculating the Hessian. The algorithm does not vary greatly by number layers. This makes it very useful as a tool to check the accuracy of other methods of determining the Hessian. For more information on the Finite Difference Method see the following article. http://en.wikipedia.org/wiki/Finite_difference_method

Field Summary

double

INITIAL_STEP The initial step size for dStep.

Fields inherited from class org.encog.mathutil.matrices.hessian.BasicHessian

derivative, flat, gradients, hessian, hessianMatrix, network, sse, training

Constructor Summary

HessianFD()

Method Summary

void	compute() Compute the Hessian.
double[]	createCoefficients() Compute finite difference coefficients according to the method provided here: http://en.wikipedia.org/wiki/Finite_difference_coefficients
int	getPointsPerSide()
void	init(BasicNetwork theNetwork, MLDataSet theTraining) Init the class.
void	setPointsPerSide(int pointsPerSide) This specifies the number of points per side, default is 5.

Methods inherited from class org.encog.mathutil.matrices.hessian.BasicHessian

clear, getGradients, getHessian, getHessianMatrix, getSSE, updateHessian

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

INITIAL_STEP

public final double INITIAL_STEP

The initial step size for dStep.

See Also:

Constant Field Values

Constructor Detail

HessianFD

public HessianFD()

Method Detail

init

public void init(BasicNetwork theNetwork,
                 MLDataSet theTraining)

Init the class.

Specified by:

init in interface ComputeHessian

Overrides:

init in class BasicHessian

Parameters:

theNetwork - The neural network to train.

theTraining - The training set to train with.

compute

public void compute()

Compute the Hessian.

createCoefficients

public double[] createCoefficients()

Compute finite difference coefficients according to the method provided here: http://en.wikipedia.org/wiki/Finite_difference_coefficients

Returns:

An array of the coefficients for FD.

getPointsPerSide

public int getPointsPerSide()

Returns:

The number of points per side.

setPointsPerSide

public void setPointsPerSide(int pointsPerSide)

This specifies the number of points per side, default is 5. Must be called before init.

Parameters:

pointsPerSide - The number of points per side.