org.encog.neural.networks.training.pnn
public class DeriveMinimum extends Object
Constructor and Description |
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DeriveMinimum() |
Modifier and Type | Method and Description |
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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.
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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)
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.Copyright © 2014. All Rights Reserved.