com.rapidminer.operator.features.construction
Class DirectedGGA

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.OperatorChain
          com.rapidminer.operator.features.construction.ExampleSetBasedFeatureOperator
              com.rapidminer.operator.features.construction.AbstractGeneratingGeneticAlgorithm
                  com.rapidminer.operator.features.construction.YAGGA
                      com.rapidminer.operator.features.construction.YAGGA2
                          com.rapidminer.operator.features.construction.DirectedGGA

All Implemented Interfaces:

ConfigurationListener, PreviewListener, ParameterHandler, LoggingHandler

public class DirectedGGA
extends YAGGA2

DirectedGGA is an acronym for a Generating Genetic Algorithm which uses probability directed search heuristics to select attributes for generation or removing. Its approach to generating new attributes differs from the original one and is the same as the one of YAGGA.
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 these mutation heuristics probablilities based on the weights of the attributes are calculated. It is more likely for attributes with a great weight to be selected for generating new attributes. On the other hand the probability for removing an attribute from the example set will decrease for attributes with great weights. This decreases the amount of needed generations drastically.
Another enhancement in comparison to the original GGA is the addition of several generators like the ones for trigonometric or exponential functions. In this way a sinple linear working learning scheme which can deliver weights can be used as inner operator. If this learner can also estimate its performance it is not longer necessary to use a inner cross-validation which also decreases learning time. Such a learner is for example the JMySVMLearner which delivers the xi-alpha performance estimation at least for classification tasks.
. Summarized the advantages of this feature construction algorithm are smaller runtimes and smaller attribute sets as result. These attribute sets increase performance and can be used to explain the models of more complex learning schemes like SVMs. The additional generators allow the construction of features which are not possible by the known kernel functions.
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 RapidMiner written by Ingo Mierswa should be used. It is available at http://rapid-i.com.

Author:

Ingo Mierswa

Field Summary

static java.lang.String	PARAMETER_MAX_GENERATED The parameter name for "The maximum number of generated attributes per generation.
static java.lang.String	PARAMETER_MAX_ORIGINAL The parameter name for "The maximum number of original attributes added per generation.

Fields inherited from class com.rapidminer.operator.features.construction.YAGGA2

PARAMETER_ASSOCIATIVE_ATTRIBUTE_MERGING, PARAMETER_CONSTANT_GENERATION_PROB, PARAMETER_EQUIVALENCE_EPSILON, PARAMETER_EQUIVALENCE_SAMPLES, PARAMETER_EQUIVALENCE_USE_STATISTICS, PARAMETER_REMOVE_EQUIVALENT, PARAMETER_REMOVE_USELESS, PARAMETER_RESTRICTIVE_SELECTION, PARAMETER_UNUSED_FUNCTIONS, PARAMETER_USE_ABSOLUTE_VALUES, PARAMETER_USE_ATAN, PARAMETER_USE_COS, PARAMETER_USE_EXP, PARAMETER_USE_FLOOR_CEIL_FUNCTIONS, PARAMETER_USE_LOG, PARAMETER_USE_MAX, PARAMETER_USE_MIN, PARAMETER_USE_POWER_FUNCTIONS, PARAMETER_USE_SGN, PARAMETER_USE_SIN, PARAMETER_USE_SQUARE_ROOTS, PARAMETER_USE_TAN

Fields inherited from class com.rapidminer.operator.features.construction.YAGGA

PARAMETER_MAX_TOTAL_NUMBER_OF_ATTRIBUTES, PARAMETER_P_MUTATION

Fields inherited from class com.rapidminer.operator.features.construction.AbstractGeneratingGeneticAlgorithm

BOLTZMANN_SELECTION, CUT_SELECTION, NON_DOMINATED_SORTING_SELECTION, PARAMETER_CROSSOVER_TYPE, PARAMETER_DYNAMIC_SELECTION_PRESSURE, PARAMETER_GENERATIONS_WITHOUT_IMPROVAL, PARAMETER_KEEP_BEST_INDIVIDUAL, PARAMETER_MAXIMUM_NUMBER_OF_GENERATIONS, PARAMETER_P_CROSSOVER, PARAMETER_P_INITIALIZE, PARAMETER_POPULATION_SIZE, PARAMETER_RECIPROCAL_VALUE, PARAMETER_START_TEMPERATURE, PARAMETER_TOURNAMENT_SIZE, PARAMETER_USE_DIFF, PARAMETER_USE_DIV, PARAMETER_USE_MULT, PARAMETER_USE_PLUS, RANK_SELECTION, ROULETTE_WHEEL, SELECTION_SCHEMES, STOCHASTIC_UNIVERSAL, TOURNAMENT_SELECTION, UNIFORM_SELECTION

Fields inherited from class com.rapidminer.operator.features.construction.ExampleSetBasedFeatureOperator

PARAMETER_LOCAL_RANDOM_SEED, PARAMETER_MAXIMAL_FITNESS, PARAMETER_SHOW_STOP_DIALOG

Constructor Summary

DirectedGGA(OperatorDescription description)

Method Summary

protected ExampleSetBasedPopulationOperator	getMutationPopulationOperator(ExampleSet eSet) Returns the DirectedGeneratingMutation.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.

Methods inherited from class com.rapidminer.operator.features.construction.YAGGA2

apply, getGenerators, getPreProcessingPopulationOperators

Methods inherited from class com.rapidminer.operator.features.construction.YAGGA

createInitialPopulation, getGeneratingPopulationOperator

Methods inherited from class com.rapidminer.operator.features.construction.AbstractGeneratingGeneticAlgorithm

getCrossoverPopulationOperator, getPostEvaluationPopulationOperators, getPostProcessingPopulationOperators, getPreEvaluationPopulationOperators, solutionGoodEnough

Methods inherited from class com.rapidminer.operator.features.construction.ExampleSetBasedFeatureOperator

evaluate, evaluate, getCheckForMaximum, getInnerOperatorCondition, getInputClasses, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getOutputClasses, getPopulation, 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_MAX_GENERATED

public static final java.lang.String PARAMETER_MAX_GENERATED

The parameter name for "The maximum number of generated attributes per generation."

See Also:

Constant Field Values

PARAMETER_MAX_ORIGINAL

public static final java.lang.String PARAMETER_MAX_ORIGINAL

The parameter name for "The maximum number of original attributes added per generation."

See Also:

Constant Field Values

Constructor Detail

DirectedGGA

public DirectedGGA(OperatorDescription description)

Method Detail

getMutationPopulationOperator

protected ExampleSetBasedPopulationOperator getMutationPopulationOperator(ExampleSet eSet)
                                                                   throws OperatorException

Returns the DirectedGeneratingMutation.

Overrides:

getMutationPopulationOperator in class YAGGA2

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 YAGGA2