jsat.math.optimization

Class NelderMead

java.lang.Object

jsat.math.optimization.NelderMead

All Implemented Interfaces:

Optimizer

public class NelderMead
extends java.lang.Object
implements Optimizer

The Nelder-Mean algorithm is a simple directed search method. As such, it does not need any information about the target functions derivative, or any data points. To perform best, the Nelder-Mean method needs N+1 reasonable initial guesses for an N dimensional problem.
The Nelder-Mean method has the advantage that the only information it needs about the function it is going to minimize, is the function itself.

Constructor Summary

Constructors

Constructor and Description
NelderMead()
NelderMead(NelderMead toCopy)

Method Summary

Modifier and Type	Method and Description
NelderMead	clone()
int	getMaximumIterations() Returns the maximum number of iterations to perform
Vec	optimize(double eps, int iterationLimit, Function f, java.util.List<Vec> initalPoints, boolean parallel) Attempts to find the minimal value of the given function.
void	optimize(double tolerance, Vec w, Vec x0, Function f, FunctionVec fp, boolean parallel) Attempts to optimize the given function by finding the value of w that will minimize the value returned by f(w), using w = x0 as an initial starting point.
void	setContraction(double contraction) Sets the contraction constant, which must be in the range (0, 1)
void	setExpansion(double expansion) Sets the expansion constant, which must be greater than 1 and the reflection constant
void	setMaximumIterations(int iterations) Sets the maximum number of iterations allowed for the optimization method
void	setReflection(double reflection) Sets the reflection constant, which must be greater than 0
void	setShrink(double shrink) Sets the shrinkage constant, which must be in the range (0, 1)

Methods inherited from class java.lang.Object

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

Methods inherited from interface jsat.math.optimization.Optimizer

optimize

Constructor Detail

NelderMead

public NelderMead()

NelderMead

public NelderMead(NelderMead toCopy)

Method Detail

setReflection

public void setReflection(double reflection)

Sets the reflection constant, which must be greater than 0

Parameters:

reflection - the reflection constant

setExpansion

public void setExpansion(double expansion)

Sets the expansion constant, which must be greater than 1 and the reflection constant

Parameters:

expansion -

setContraction

public void setContraction(double contraction)

Sets the contraction constant, which must be in the range (0, 1)

Parameters:

contraction - the contraction constant

setShrink

public void setShrink(double shrink)

Sets the shrinkage constant, which must be in the range (0, 1)

Parameters:

shrink -

optimize

public void optimize(double tolerance,
                     Vec w,
                     Vec x0,
                     Function f,
                     FunctionVec fp,
                     boolean parallel)

Description copied from interface: Optimizer

Attempts to optimize the given function by finding the value of w that will minimize the value returned by f(w), using w = x₀ as an initial starting point.

Specified by:

optimize in interface Optimizer

Parameters:

tolerance - the value that the gradient norm must be less than to consider converged

w - the the location to store the final solution

x0 - the initial guess for the solution. This value will not be changed, and intermediate matrices will be created as the same type.

f - the objective function to minimizer

fp - the derivative of the objective function, may be null depending on the optimizer

parallel - true if multiple threads should be used for optimization, or false if a single thread should be used.

optimize

public Vec optimize(double eps,
                    int iterationLimit,
                    Function f,
                    java.util.List<Vec> initalPoints,
                    boolean parallel)

Attempts to find the minimal value of the given function.

Parameters:

eps - the desired accuracy of the result.

iterationLimit - the maximum number of iteration steps to allow. This value must be positive

f - the function to optimize. This value can not be null

initalPoints - the list of initial guess points. If too small, new ones will be generated. if too large, the extra ones will be ignored. This list may not be empty

parallel - true if multiple threads should be used for optimization, or false if a single thread should be used.

Returns:

the computed value for the optimization.

setMaximumIterations

public void setMaximumIterations(int iterations)

Description copied from interface: Optimizer

Sets the maximum number of iterations allowed for the optimization method

Specified by:

setMaximumIterations in interface Optimizer

Parameters:

iterations - the maximum number of iterations to perform

getMaximumIterations

public int getMaximumIterations()

Description copied from interface: Optimizer

Returns the maximum number of iterations to perform

Specified by:

getMaximumIterations in interface Optimizer

Returns:

the maximum number of iterations to perform

clone

public NelderMead clone()

Specified by:

clone in interface Optimizer

Overrides:

clone in class java.lang.Object