com.rapidminer.operator.features.selection
Class WeightGuidedSelectionOperator

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.OperatorChain
          com.rapidminer.operator.features.FeatureOperator
              com.rapidminer.operator.features.selection.WeightGuidedSelectionOperator

All Implemented Interfaces:

ConfigurationListener, PreviewListener, ParameterHandler, LoggingHandler

public class WeightGuidedSelectionOperator
extends FeatureOperator

This operator uses input attribute weights to determine the order of features added to the feature set starting with the feature set containing only the feature with highest weight. The inner operators must provide a performance vector to determine the fitness of the current feature set, e.g. a cross validation of a learning scheme for a wrapper evaluation. Stops if adding the last k features does not increase the performance or if all features were added. The value of k can be set with the parameter generations_without_improval.

Author:

Ingo Mierswa ingomierswa Exp $

Field Summary

static java.lang.String	PARAMETER_GENERATIONS_WITHOUT_IMPROVAL The parameter name for "Stop after n generations without improval of the performance (-1: stops if the number of features is reached).
static java.lang.String	PARAMETER_USE_ABSOLUTE_WEIGHTS The parameter name for "Indicates that the absolute values of the input weights should be used to determine the feature adding order.

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

WeightGuidedSelectionOperator(OperatorDescription description)

Method Summary

Population	createInitialPopulation(ExampleSet es) Returns an example set containing only the feature with the biggest weight.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.
java.util.List<PopulationOperator>	getPostEvaluationPopulationOperators(ExampleSet input) Returns an empty list.
java.util.List<PopulationOperator>	getPreEvaluationPopulationOperators(ExampleSet input) The operators add the feature with the next highest weight.
boolean	solutionGoodEnough(Population pop) Returns true if the best individual is not better than the last generation's best individual.

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_GENERATIONS_WITHOUT_IMPROVAL

public static final java.lang.String PARAMETER_GENERATIONS_WITHOUT_IMPROVAL

The parameter name for "Stop after n generations without improval of the performance (-1: stops if the number of features is reached)."

See Also:

Constant Field Values

PARAMETER_USE_ABSOLUTE_WEIGHTS

public static final java.lang.String PARAMETER_USE_ABSOLUTE_WEIGHTS

The parameter name for "Indicates that the absolute values of the input weights should be used to determine the feature adding order."

See Also:

Constant Field Values

Constructor Detail

WeightGuidedSelectionOperator

public WeightGuidedSelectionOperator(OperatorDescription description)

Method Detail

createInitialPopulation

public Population createInitialPopulation(ExampleSet es)
                                   throws UndefinedParameterError

Returns an example set containing only the feature with the biggest weight.

Specified by:

createInitialPopulation in class FeatureOperator

Throws:

UndefinedParameterError

getPreEvaluationPopulationOperators

public java.util.List<PopulationOperator> getPreEvaluationPopulationOperators(ExampleSet input)
                                                                       throws OperatorException

The operators add the feature with the next highest weight.

Specified by:

getPreEvaluationPopulationOperators in class FeatureOperator

Throws:

OperatorException

getPostEvaluationPopulationOperators

public java.util.List<PopulationOperator> getPostEvaluationPopulationOperators(ExampleSet input)
                                                                        throws OperatorException

Returns an empty list.

Specified by:

getPostEvaluationPopulationOperators in class FeatureOperator

Throws:

OperatorException

solutionGoodEnough

public boolean solutionGoodEnough(Population pop)
                           throws OperatorException

Returns true if the best individual is not better than the last generation's best individual.

Specified by:

solutionGoodEnough 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.

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class FeatureOperator