org.gersteinlab.regulation.numeric
Class GradientDescent
java.lang.Object
org.gersteinlab.regulation.numeric.DescentMethod
org.gersteinlab.regulation.numeric.GradientDescent
public class GradientDescent
- extends DescentMethod
A class for minimizing a differentiable multivariate real function using
gradient descent.
- Version:
- 1.0 (September 4, 2008)
Change History:
1.0 - Initial version
- Author:
- Kevin Yuk-Lap Yip
Field Summary |
static double |
ETA
|
Method Summary |
double[] |
minimize(double[] x0)
Perform the minimization using default parameters. |
double[] |
minimize(double[] x0,
double alpha,
double beta,
double eta)
Perform the minimization. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
ETA
public static final double ETA
- See Also:
- Constant Field Values
GradientDescent
public GradientDescent(DifferentiableMultivariateFunction funcIn)
- Construct an instance for a function.
- Parameters:
funcIn
- The function
minimize
public double[] minimize(double[] x0)
- Perform the minimization using default parameters.
- Specified by:
minimize
in class DescentMethod
- Parameters:
x0
- The initial estimate of x
- Returns:
- The final estimate of x
minimize
public double[] minimize(double[] x0,
double alpha,
double beta,
double eta)
- Perform the minimization.
- Parameters:
x0
- The initial estimate of xalpha
- The stopping parameter of backtracking line searchbeta
- The reduction factor of t of backtracking line searcheta
- The stopping parameter
- Returns:
- The final estimate of x