Documentation of 'org.encog.mathutil.matrices.hessian.HessianFD' Java class
HessianFD
org.encog.mathutil.matrices.hessian

Class 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 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.

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