gov.sandia.cognition.learning.algorithm.minimization

Class AbstractAnytimeFunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm<ResultType>

gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner<EvaluatorType,InputOutputPair<InputType,OutputType>>

gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer<InputType,OutputType,EvaluatorType>

Type Parameters:

InputType - Input class of the Evaluator that we are trying to minimize, such as Vector

OutputType - Output class of the Evaluator that we are trying to minimize, such as Double

EvaluatorType - Evaluator class that this minimization algorithm can handle, such as Evaluator or DifferentiableEvaluator.

All Implemented Interfaces:

AnytimeAlgorithm<InputOutputPair<InputType,OutputType>>, IterativeAlgorithm, StoppableAlgorithm, AnytimeBatchLearner<EvaluatorType,InputOutputPair<InputType,OutputType>>, BatchLearner<EvaluatorType,InputOutputPair<InputType,OutputType>>, FunctionMinimizer<InputType,OutputType,EvaluatorType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

AbstractAnytimeLineMinimizer, FunctionMinimizerConjugateGradient, FunctionMinimizerDirectionSetPowell, FunctionMinimizerGradientDescent, FunctionMinimizerNelderMead, FunctionMinimizerQuasiNewton

public abstract class AbstractAnytimeFunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>
extends AbstractAnytimeBatchLearner<EvaluatorType,InputOutputPair<InputType,OutputType>>
implements FunctionMinimizer<InputType,OutputType,EvaluatorType>

A partial implementation of a minimization algorithm that is iterative, stoppable, and approximate.

Since:

2.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected InputType	initialGuess Initial guess of the minimization routine
protected InputOutputPair<InputType,OutputType>	result Resulting minimum input-output pair
protected double	tolerance Tolerance of the minimization algorithm, must be >= 0.0

Fields inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

data, keepGoing

Fields inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

maxIterations

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

DEFAULT_ITERATION, iteration

Constructor Summary

Constructors

Constructor and Description
AbstractAnytimeFunctionMinimizer(InputType initialGuess, double tolerance, int maxIterations) Creates a new instance of AbstractStandardIterativeMinimizationAlgorithm

Method Summary

Modifier and Type	Method and Description
InputType	getInitialGuess() Getter for initialGuess
InputOutputPair<InputType,OutputType>	getResult() Getter for result
double	getTolerance() Getter for tolerance
void	setInitialGuess(InputType initialGuess) Setter for initialGuess
protected void	setResult(InputOutputPair<InputType,OutputType> result) Setter for result
void	setTolerance(double tolerance) Setter for tolerance

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

cleanupAlgorithm, clone, getData, getKeepGoing, initializeAlgorithm, learn, setData, setKeepGoing, step, stop

Methods inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

getMaxIterations, isResultValid, setMaxIterations

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getIteration, getListeners, removeIterativeAlgorithmListener, setIteration, setListeners

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizer

learn

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.algorithm.AnytimeAlgorithm

getMaxIterations, setMaxIterations

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm

addIterativeAlgorithmListener, getIteration, removeIterativeAlgorithmListener

Methods inherited from interface gov.sandia.cognition.algorithm.StoppableAlgorithm

isResultValid, stop

Field Detail

tolerance

protected double tolerance

Tolerance of the minimization algorithm, must be >= 0.0

result

protected InputOutputPair<InputType,OutputType> result

Resulting minimum input-output pair

initialGuess

protected InputType initialGuess

Initial guess of the minimization routine

Constructor Detail

AbstractAnytimeFunctionMinimizer

public AbstractAnytimeFunctionMinimizer(InputType initialGuess,
                                        double tolerance,
                                        int maxIterations)

Creates a new instance of AbstractStandardIterativeMinimizationAlgorithm

Parameters:

initialGuess - Initial guess of the minimization routine

tolerance - Tolerance of the minimization algorithm, must be >= 0.0

maxIterations - Maximum number of iterations to run before stopping

Method Detail

getResult

public InputOutputPair<InputType,OutputType> getResult()

Getter for result

Specified by:

getResult in interface AnytimeAlgorithm<InputOutputPair<InputType,OutputType>>

Returns:

Resulting minimum input-output pair

setResult

protected void setResult(InputOutputPair<InputType,OutputType> result)

Setter for result

Parameters:

result - Resulting minimum input-output pair

getTolerance

public double getTolerance()

Getter for tolerance

Specified by:

getTolerance in interface FunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>

Returns:

Tolerance of the minimization algorithm, must be >= 0.0

setTolerance

public void setTolerance(double tolerance)

Setter for tolerance

Specified by:

setTolerance in interface FunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>

Parameters:

tolerance - Tolerance of the minimization algorithm, must be >= 0.0

getInitialGuess

public InputType getInitialGuess()

Getter for initialGuess

Specified by:

getInitialGuess in interface FunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>

Returns:

Initial guess of the minimization routine

setInitialGuess

public void setInitialGuess(InputType initialGuess)

Setter for initialGuess

Specified by:

setInitialGuess in interface FunctionMinimizer<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>

Parameters:

initialGuess - Initial guess of the minimization routine