com.rapidminer.operator.features.weighting
Class EvolutionaryWeighting

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.OperatorChain
          com.rapidminer.operator.features.FeatureOperator
              com.rapidminer.operator.features.selection.AbstractGeneticAlgorithm
                  com.rapidminer.operator.features.weighting.EvolutionaryWeighting

All Implemented Interfaces:

ConfigurationListener, PreviewListener, ParameterHandler, LoggingHandler

public class EvolutionaryWeighting
extends AbstractGeneticAlgorithm

This operator performs the weighting of features with an evolutionary strategies approach. The variance of the gaussian additive mutation can be adapted by a 1/5-rule.

Author:

Ingo Mierswa ingomierswa Exp $

Field Summary

static java.lang.String	PARAMETER_1_5_RULE The parameter name for "If set to true, the 1/5 rule for variance adaption is used.
static java.lang.String	PARAMETER_BOUNDED_MUTATION The parameter name for "If set to true, the weights are bounded between 0 and 1.
static java.lang.String	PARAMETER_CROSSOVER_TYPE The parameter name for "Type of the crossover.
static java.lang.String	PARAMETER_INITIALIZE_WITH_INPUT_WEIGHTS
static java.lang.String	PARAMETER_MUTATION_VARIANCE The parameter name for "The (initial) variance for each mutation.
static java.lang.String	PARAMETER_P_CROSSOVER The parameter name for "Probability for an individual to be selected for crossover.

Fields inherited from class com.rapidminer.operator.features.selection.AbstractGeneticAlgorithm

BOLTZMANN_SELECTION, CUT_SELECTION, NON_DOMINATED_SORTING_SELECTION, PARAMETER_DYNAMIC_SELECTION_PRESSURE, PARAMETER_GENERATIONS_WITHOUT_IMPROVAL, PARAMETER_INTERMEDIATE_WEIGHTS_FILE, PARAMETER_INTERMEDIATE_WEIGHTS_GENERATIONS, PARAMETER_KEEP_BEST_INDIVIDUAL, PARAMETER_MAXIMUM_NUMBER_OF_GENERATIONS, PARAMETER_POPULATION_SIZE, PARAMETER_SAVE_INTERMEDIATE_WEIGHTS, PARAMETER_SELECTION_SCHEME, PARAMETER_START_TEMPERATURE, PARAMETER_TOURNAMENT_SIZE, RANK_SELECTION, ROULETTE_WHEEL, SELECTION_SCHEMES, STOCHASTIC_UNIVERSAL, TOURNAMENT_SELECTION, UNIFORM_SELECTION

Fields inherited from class com.rapidminer.operator.features.FeatureOperator

PARAMETER_CONSTRAINT_DRAW_RANGE, PARAMETER_DRAW_DOMINATED_POINTS, PARAMETER_LOCAL_RANDOM_SEED, PARAMETER_MAXIMAL_FITNESS, PARAMETER_NORMALIZE_WEIGHTS, PARAMETER_PLOT_GENERATIONS, PARAMETER_POPULATION_CRITERIA_DATA_FILE, PARAMETER_SHOW_POPULATION_PLOTTER, PARAMETER_SHOW_STOP_DIALOG, PARAMETER_USER_RESULT_INDIVIDUAL_SELECTION

Constructor Summary

EvolutionaryWeighting(OperatorDescription description)

Method Summary

Population	createInitialPopulation(ExampleSet exampleSet) Create an initial population.
PopulationOperator	getCrossoverPopulationOperator(ExampleSet eSet) Returns an operator that performs crossover.
PopulationOperator	getMutationPopulationOperator(ExampleSet eSet) Returns an operator that performs the mutation.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.
protected java.util.List<PopulationOperator>	getPostProcessingPopulationOperators(ExampleSet eSet) Returns an empty list.

Methods inherited from class com.rapidminer.operator.features.selection.AbstractGeneticAlgorithm

getPostEvaluationPopulationOperators, getPreEvaluationPopulationOperators, getPreProcessingPopulationOperators, solutionGoodEnough

Methods inherited from class com.rapidminer.operator.features.FeatureOperator

apply, createCleanClone, evaluate, getCheckForMaximum, getInnerOperatorCondition, getInputClasses, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getOutputClasses, getPopulation, getPopulationEvaluator, getRandom, setCheckForMaximum

Methods inherited from class com.rapidminer.operator.OperatorChain

addAddListener, addOperator, addOperator, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clearErrorList, cloneOperator, createExperimentTree, createProcessTree, getAllInnerOperators, getIndexOfOperator, getInnerOperatorForName, getInnerOperatorsXML, getNumberOfAllOperators, getNumberOfOperators, getOperator, getOperatorFromAll, getOperators, performAdditionalChecks, processFinished, processStarts, registerOperator, removeAddListener, removeOperator, shouldAddNonConsumedInput, shouldReturnInnerOutput, unregisterOperator

Methods inherited from class com.rapidminer.operator.Operator

addError, addValue, addWarning, apply, checkForStop, createExperimentTree, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getEncoding, getErrorList, getExperiment, getInput, getInput, getInput, getInputDescription, getIOContainerForInApplyLoopBreakpoint, getIODescription, getLog, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getProcess, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isEnabled, isExpanded, isParallel, isParameterSet, log, logError, logNote, logWarning, register, remove, rename, resume, setApplyCount, setBreakpoint, setEnabled, setExpanded, 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

Field Detail

PARAMETER_MUTATION_VARIANCE

public static final java.lang.String PARAMETER_MUTATION_VARIANCE

The parameter name for "The (initial) variance for each mutation."

See Also:

Constant Field Values

PARAMETER_1_5_RULE

public static final java.lang.String PARAMETER_1_5_RULE

The parameter name for "If set to true, the 1/5 rule for variance adaption is used."

See Also:

Constant Field Values

PARAMETER_BOUNDED_MUTATION

public static final java.lang.String PARAMETER_BOUNDED_MUTATION

The parameter name for "If set to true, the weights are bounded between 0 and 1."

See Also:

Constant Field Values

PARAMETER_P_CROSSOVER

public static final java.lang.String PARAMETER_P_CROSSOVER

The parameter name for "Probability for an individual to be selected for crossover."

See Also:

Constant Field Values

PARAMETER_CROSSOVER_TYPE

public static final java.lang.String PARAMETER_CROSSOVER_TYPE

The parameter name for "Type of the crossover."

See Also:

Constant Field Values

PARAMETER_INITIALIZE_WITH_INPUT_WEIGHTS

public static final java.lang.String PARAMETER_INITIALIZE_WITH_INPUT_WEIGHTS

See Also:

Constant Field Values

Constructor Detail

EvolutionaryWeighting

public EvolutionaryWeighting(OperatorDescription description)

Method Detail

getCrossoverPopulationOperator

public PopulationOperator getCrossoverPopulationOperator(ExampleSet eSet)
                                                  throws UndefinedParameterError

Description copied from class: AbstractGeneticAlgorithm

Returns an operator that performs crossover. Can be overridden by subclasses.

Specified by:

getCrossoverPopulationOperator in class AbstractGeneticAlgorithm

Throws:

UndefinedParameterError

getMutationPopulationOperator

public PopulationOperator getMutationPopulationOperator(ExampleSet eSet)
                                                 throws UndefinedParameterError

Description copied from class: AbstractGeneticAlgorithm

Returns an operator that performs the mutation. Can be overridden by subclasses.

Specified by:

getMutationPopulationOperator in class AbstractGeneticAlgorithm

Throws:

UndefinedParameterError

getPostProcessingPopulationOperators

protected java.util.List<PopulationOperator> getPostProcessingPopulationOperators(ExampleSet eSet)
                                                                           throws UndefinedParameterError

Description copied from class: AbstractGeneticAlgorithm

Returns an empty list.

Overrides:

getPostProcessingPopulationOperators in class AbstractGeneticAlgorithm

Throws:

UndefinedParameterError

createInitialPopulation

public Population createInitialPopulation(ExampleSet exampleSet)
                                   throws UndefinedParameterError

Description copied from class: FeatureOperator

Create an initial population. The example set will be cloned before the method is invoked. This method is invoked after the pre- and postevaluation population operators were collected.

Specified by:

createInitialPopulation in class FeatureOperator

Throws:

UndefinedParameterError

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.

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class AbstractGeneticAlgorithm