gov.sandia.cognition.learning.algorithm.regression
Class ParameterDerivativeFreeCostMinimizer

java.lang.Object
  gov.sandia.cognition.util.AbstractCloneableSerializable
      gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
          gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper<ResultType,FunctionMinimizer<Vector,Double,? super EvaluatorType>>
              gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,Double,Vector>>
                  gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer

All Implemented Interfaces:

AnytimeAlgorithm<VectorizableVectorFunction>, IterativeAlgorithm, IterativeAlgorithmListener, MeasurablePerformanceAlgorithm, StoppableAlgorithm, BatchCostMinimizationLearner<Collection<? extends InputOutputPair<? extends Vector,Vector>>,VectorizableVectorFunction>, BatchLearner<Collection<? extends InputOutputPair<? extends Vector,Vector>>,VectorizableVectorFunction>, ParameterCostMinimizer<VectorizableVectorFunction>, SupervisedBatchLearner<Vector,Vector,VectorizableVectorFunction>, CloneableSerializable, Serializable, Cloneable

public class ParameterDerivativeFreeCostMinimizer
extends AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,Double,Vector>>

Implementation of a class of objects that uses a derivative-free minimization algorithm. That is, this class estimates locally minimum-cost parameter sets without needing first-order derivative information.

Since:

2.1

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

static class

ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree Function that maps the parameters of an object to its inputs, so that minimization algorithms can tune the parameters of an object against a cost function.

Field Summary

static FunctionMinimizer<Vector,Double,Evaluator<? super Vector,Double>>

DEFAULT_FUNCTION_MINIMIZER Default function minimizer, FunctionMinimizerDirectionSetPowell

Fields inherited from class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer

DEFAULT_COST_FUNCTION

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

DEFAULT_ITERATION, iteration

Constructor Summary

ParameterDerivativeFreeCostMinimizer()
Creates a new instance of ParameterDerivativeFreeCostMinimizer

ParameterDerivativeFreeCostMinimizer(FunctionMinimizer<Vector,Double,? super DifferentiableEvaluator<Vector,Double,Vector>> minimizer)
Creates a new instance of ParameterDerivativeFreeCostMinimizer

Method Summary

ParameterDerivativeFreeCostMinimizer	clone() This makes public the clone method on the Object class and removes the exception that it throws.
ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree	createInternalFunction() Creates the internal function that maps the parameter set of result as the input to the function, so that the minimization algorithms can perturb this input in their minimization schemes.

Methods inherited from class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer

getCostFunction, getObjectToOptimize, getPerformance, getResult, learn, setCostFunction, setObjectToOptimize, setResult

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

algorithmEnded, algorithmStarted, getAlgorithm, getIteration, getMaxIterations, isResultValid, readResolve, setAlgorithm, setMaxIterations, stepEnded, stepStarted, stop

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

addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, 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.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

DEFAULT_FUNCTION_MINIMIZER

public static final FunctionMinimizer<Vector,Double,Evaluator<? super Vector,Double>> DEFAULT_FUNCTION_MINIMIZER

Default function minimizer, FunctionMinimizerDirectionSetPowell

Constructor Detail

ParameterDerivativeFreeCostMinimizer

public ParameterDerivativeFreeCostMinimizer()

Creates a new instance of ParameterDerivativeFreeCostMinimizer

ParameterDerivativeFreeCostMinimizer

public ParameterDerivativeFreeCostMinimizer(FunctionMinimizer<Vector,Double,? super DifferentiableEvaluator<Vector,Double,Vector>> minimizer)

Creates a new instance of ParameterDerivativeFreeCostMinimizer

Parameters:

minimizer - Minimization algorithm used to find locally optimal parameters

Method Detail

clone

public ParameterDerivativeFreeCostMinimizer clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,Double,Vector>>

Returns:

A clone of this object.

createInternalFunction

public ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree createInternalFunction()

Description copied from class: AbstractMinimizerBasedParameterCostMinimizer

Creates the internal function that maps the parameter set of result as the input to the function, so that the minimization algorithms can perturb this input in their minimization schemes.

Specified by:

createInternalFunction in class AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,Double,Vector>>

Returns:

Evaluator to use internally.