com.rapidminer.operator.features.weighting
Class EvolutionaryWeighting

java.lang.Object
  com.rapidminer.tools.AbstractObservable<Operator>
      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, ResourceConsumer, ParameterHandler, LoggingHandler, Observable<Operator>

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, Sebastian Land

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_DEFAULT_NOMINAL_MUTATION_RATE
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_NOMINAL_MUTATION_RATE
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, PARAMETER_USE_EARLY_STOPPING, 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_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.
void	doWork() 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
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

createCleanClone, executeEvaluationProcess, getCheckForMaximum, getExampleSetInput, getPopulation, getPopulationEvaluator, getRandom, modifyInnerOutputExampleSet, modifyOutputExampleSet, runEvaluationProcess, setCheckForMaximum

Methods inherited from class com.rapidminer.operator.OperatorChain

addOperator, addOperator, addSubprocess, areSubprocessesExtendable, assumePreconditionsSatisfied, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clear, cloneOperator, collectErrors, createProcessTree, createSubprocess, freeMemory, getAllInnerOperators, getAllInnerOperatorsAndMe, getImmediateChildren, getIndexOfOperator, getInnerOperatorCondition, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getNumberOfAllOperators, getNumberOfOperators, getNumberOfSubprocesses, getOperator, getOperatorFromAll, getOperators, getSubprocess, getSubprocesses, isEnabled, lookupOperator, notifyRenaming, performAdditionalChecks, processFinished, processStarts, propagateDirtyness, registerOperator, removeOperator, removeSubprocess, shouldAddNonConsumedInput, shouldReturnInnerOutput, unregisterOperator, updateExecutionOrder, walk

Methods inherited from class com.rapidminer.operator.Operator

acceptsInput, addError, addError, addValue, addWarning, apply, apply, checkAll, checkAllExcludingMetaData, checkForStop, clearErrorList, createExperimentTree, createExperimentTree, createFromXML, createFromXML, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, disconnectPorts, execute, fireUpdate, getAddOnlyAdditionalOutput, getApplyCount, getCompatibilityLevel, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getDOMRepresentation, getEncoding, getErrorList, getExecutionUnit, getExperiment, getIncompatibleVersionChanges, getInput, getInput, getInput, getInputClasses, getInputDescription, getInputPorts, getIODescription, getLog, getLogger, getName, getNumberOfBreakpoints, getOperatorClassName, getOperatorDescription, getOutputClasses, getOutputPorts, getParameter, getParameterAsBoolean, getParameterAsChar, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsRepositoryLocation, getParameterAsString, getParameterHandler, getParameterList, getParameters, getParameterTupel, getParameterType, getParent, getPortOwner, getProcess, getResourceConsumptionEstimator, getRoot, getStartTime, getTransformer, getUserDescription, getValue, getValues, getXML, getXML, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isDirty, isExpanded, isParallel, isParameterSet, isRunning, log, log, logError, logNote, logWarning, makeDirty, makeDirtyOnUpdate, preAutoWire, producesOutput, register, remove, removeAndKeepConnections, rename, resume, setBreakpoint, setCompatibilityLevel, setEnabled, setEnclosingProcess, setExpanded, setInput, setListParameter, setPairParameter, setParameter, setParameters, setUserDescription, shouldAutoConnect, shouldAutoConnect, shouldStopStandaloneExecution, toString, transformMetaData, writeXML, writeXML

Methods inherited from class com.rapidminer.tools.AbstractObservable

addObserver, addObserverAsFirst, fireUpdate, removeObserver

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

PARAMETER_NOMINAL_MUTATION_RATE

public static final java.lang.String PARAMETER_NOMINAL_MUTATION_RATE

See Also:

Constant Field Values

PARAMETER_DEFAULT_NOMINAL_MUTATION_RATE

public static final java.lang.String PARAMETER_DEFAULT_NOMINAL_MUTATION_RATE

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

doWork

public void doWork()
            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:

doWork in class FeatureOperator

Throws:

OperatorException

createInitialPopulation

public Population createInitialPopulation(ExampleSet exampleSet)
                                   throws OperatorException

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:

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. ATTENTION! This will create new parameterTypes. For calling already existing parameter types use getParameters().getParameterTypes();

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class AbstractGeneticAlgorithm