org.encog.neural.networks.training.pnn
Class DeriveMinimum

java.lang.Object
  org.encog.neural.networks.training.pnn.DeriveMinimum

public class DeriveMinimum
extends Object

This class determines optimal values for multiple sigmas in a PNN kernel. This is done using a CJ (conjugate gradient) method. Some of the algorithms in this class are based on C++ code from: Advanced Algorithms for Neural Networks: A C++ Sourcebook by Timothy Masters John Wiley & Sons Inc (Computers); April 3, 1995 ISBN: 0471105880

Constructor Summary

DeriveMinimum()

Method Summary

double

calculate(int maxIterations, double maxError, double eps, double tol, CalculationCriteria network, int n, double[] x, double ystart, double[] base, double[] direc, double[] g, double[] h, double[] deriv2) Derive the minimum, using a conjugate gradient method.

Methods inherited from class java.lang.Object

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

Constructor Detail

DeriveMinimum

public DeriveMinimum()

Method Detail

calculate

public double calculate(int maxIterations,
                        double maxError,
                        double eps,
                        double tol,
                        CalculationCriteria network,
                        int n,
                        double[] x,
                        double ystart,
                        double[] base,
                        double[] direc,
                        double[] g,
                        double[] h,
                        double[] deriv2)

Derive the minimum, using a conjugate gradient method.

Parameters:

maxIterations - The max iterations.

maxError - Stop at this error rate.

eps - The machine's precision.

tol - The convergence tolerance.

network - The network to get the error from.

n - The number of variables.

x - The independent variable.

ystart - The start for y.

base - Work vector, must have n elements.

direc - Work vector, must have n elements.

g - Work vector, must have n elements.

h - Work vector, must have n elements.

deriv2 - Work vector, must have n elements.

Returns:

The best error.