edu.udo.cs.yale.operator.features.construction
Class YAGGA2

java.lang.Object
  edu.udo.cs.yale.operator.Operator
      edu.udo.cs.yale.operator.OperatorChain
          edu.udo.cs.yale.operator.features.FeatureOperator
              edu.udo.cs.yale.operator.features.selection.AbstractGeneticAlgorithm
                  edu.udo.cs.yale.operator.features.construction.AbstractGeneratingGeneticAlgorithm
                      edu.udo.cs.yale.operator.features.construction.YAGGA
                          edu.udo.cs.yale.operator.features.construction.YAGGA2

All Implemented Interfaces:

ConfigurationListener

Direct Known Subclasses:

DirectedGGA, FourierGGA

public class YAGGA2
extends YAGGA

YAGGA is an acronym for Yet Another Generating Genetic Algorithm. Its approach to generating new attributes differs from the original one. The (generating) mutation can do one of the following things with different probabilities:

• Probability p/4: Add a newly generated attribute to the feature vector
• Probability p/4: Add a randomly chosen original attribute to the feature vector
• Probability p/2: Remove a randomly chosen attribute from the feature vector

Thus it is guaranteed that the length of the feature vector can both grow and shrink. On average it will keep its original length, unless longer or shorter individuals prove to have a better fitness.

In addition to the usual YAGGA operator, this operator allows more feature generators and provides several techniques for intron prevention. This leads to smaller example sets containing less redundant features.

Since this operator does not contain algorithms to extract features from value series, it is restricted to example sets with only single attributes. For (automatic) feature extraction from values series the value series plugin for Yale should be used.

For more information please refer to

Mierswa, Ingo (2006): RobustGP: Intron-Free Multi-Objective Feature Construction (to appear)

Version:

$Id: YAGGA2.java,v 1.6 2006/10/02 21:45:26 ingomierswa Exp $

Author:

Ingo Mierswa

Field Summary

Fields inherited from class edu.udo.cs.yale.operator.features.selection.AbstractGeneticAlgorithm

BOLTZMANN_SELECTION, CUT_SELECTION, NON_DOMINATED_SORTING_SELECTION, RANK_SELECTION, ROULETTE_WHEEL, SELECTION_SCHEMES, STOCHASTIC_UNIVERSAL, TOURNAMENT_SELECTION, UNIFORM_SELECTION

Constructor Summary

YAGGA2(OperatorDescription description)

Method Summary

IOObject[]	apply() Applies the feature operator: collects the pre- and postevaluation operators create an initial population evaluate the initial population loop as long as solution is not good enough apply all pre evaluation operators evaluate the population update the population's best individual apply all post evaluation operators return all generation's best individual
java.util.List<FeatureGenerator>	getGenerators() Returns a list with all generator which should be used.
protected PopulationOperator	getMutationPopulationOperator(ExampleSet exampleSet) Returns the generating mutation PopulationOperator.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.
protected java.util.List<PopulationOperator>	getPreProcessingPopulationOperators(ExampleSet eSet) Returns an empty list.

Methods inherited from class edu.udo.cs.yale.operator.features.construction.YAGGA

createInitialPopulation, getGeneratingPopulationOperator

Methods inherited from class edu.udo.cs.yale.operator.features.construction.AbstractGeneratingGeneticAlgorithm

getCrossoverPopulationOperator

Methods inherited from class edu.udo.cs.yale.operator.features.selection.AbstractGeneticAlgorithm

getPostEvaluationPopulationOperators, getPostProcessingPopulationOperators, getPreEvaluationPopulationOperators, solutionGoodEnough

Methods inherited from class edu.udo.cs.yale.operator.features.FeatureOperator

evaluate, evaluate, getCheckForMaximum, getInnerOperatorCondition, getInputClasses, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getNumberOfSteps, getOutputClasses, getRandom, setCheckForMaximum

Methods inherited from class edu.udo.cs.yale.operator.OperatorChain

addAddListener, addOperator, addOperator, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clearErrorList, clearStepCounter, cloneOperator, countStep, createExperimentTree, delete, experimentFinished, experimentStarts, getAllInnerOperators, getCurrentStep, getIndexOfOperator, getInnerOperatorForName, getInnerOperatorsXML, getNumberOfAllOperators, getNumberOfChildrensSteps, getNumberOfOperators, getOperator, getOperatorFromAll, getOperators, isEnabled, performAdditionalChecks, removeAddListener, removeOperator, setEnabled, setExperiment, shouldReturnInnerOutput

Methods inherited from class edu.udo.cs.yale.operator.Operator

addError, addValue, addWarning, apply, createExperimentTree, createFromXML, createMarkedExperimentTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getErrorList, getExperiment, getInput, getInput, getInput, getInputDescription, getIOContainerForInApplyLoopBreakpoint, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsInt, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isParameterSet, logMessage, register, remove, rename, resume, setBreakpoint, setInput, setListParameter, setOperatorParameters, setParameter, setParameters, setParent, setUserDescription, toString, writeXML

Methods inherited from class java.lang.Object

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

Constructor Detail

YAGGA2

public YAGGA2(OperatorDescription description)

Method Detail

apply

public IOObject[] apply()
                 throws OperatorException

Description copied from class: FeatureOperator

Applies the feature operator:

1. collects the pre- and postevaluation operators
2. create an initial population
3. evaluate the initial population
4. loop as long as solution is not good enough
   1. apply all pre evaluation operators
   2. evaluate the population
   3. update the population's best individual
   4. apply all post evaluation operators
5. return all generation's best individual

Overrides:

apply in class FeatureOperator

Returns:

the last inner operator's output or the input itself if the chain is empty.

Throws:

OperatorException

getMutationPopulationOperator

protected PopulationOperator getMutationPopulationOperator(ExampleSet exampleSet)
                                                    throws OperatorException

Description copied from class: YAGGA

Returns the generating mutation PopulationOperator.

Overrides:

getMutationPopulationOperator in class YAGGA

Throws:

OperatorException

getGenerators

public java.util.List<FeatureGenerator> getGenerators()

Description copied from class: AbstractGeneratingGeneticAlgorithm

Returns a list with all generator which should be used.

Overrides:

getGenerators in class AbstractGeneratingGeneticAlgorithm

getPreProcessingPopulationOperators

protected java.util.List<PopulationOperator> getPreProcessingPopulationOperators(ExampleSet eSet)
                                                                          throws OperatorException

Description copied from class: AbstractGeneticAlgorithm

Returns an empty list.

Overrides:

getPreProcessingPopulationOperators in class AbstractGeneratingGeneticAlgorithm

Throws:

OperatorException

getParameterTypes

public java.util.List<ParameterType> getParameterTypes()

Description copied from class: Operator

Returns a list of ParameterTypes describing the parameters of this operator. The default implementation returns an empty list if no input objects can be retained and special parameters for those input objects which can be prevented from being consumed.

Overrides:

getParameterTypes in class YAGGA