org.dllearner.core.configurators
Class ISLEConfigurator

java.lang.Object
  org.dllearner.core.configurators.RefinementOperatorConfigurator
      org.dllearner.core.configurators.ISLEConfigurator

All Implemented Interfaces:

Configurator

public class ISLEConfigurator
extends RefinementOperatorConfigurator
implements Configurator

automatically generated, do not edit manually. run org.dllearner.scripts.ConfigJavaGenerator to update

Constructor Summary

ISLEConfigurator(ISLE iSLE)

Method Summary

int	getCardinalityLimit() cardinalityLimit Gives the maximum number used in cardinality restrictions..
boolean	getFilterDescriptionsFollowingFromKB() filterDescriptionsFollowingFromKB If true, then the results will not contain suggestions, which already follow logically from the knowledge base.
boolean	getInstanceBasedDisjoints() instanceBasedDisjoints Specifies whether to use real disjointness checks or instance based ones (no common instances) in the refinement operator..
static ISLE	getISLE(AbstractLearningProblem learningProblem, AbstractReasonerComponent reasoningService)
int	getMaxDepth() maxDepth maximum depth of description.
int	getMaxExecutionTimeInSeconds() maxExecutionTimeInSeconds algorithm will stop after specified seconds.
int	getMaxNrOfResults() maxNrOfResults Sets the maximum number of results one is interested in.
double	getNoisePercentage() noisePercentage the (approximated) percentage of noise within the examples.
boolean	getReuseExistingDescription() reuseExistingDescription If true, the algorithm tries to find a good starting point close to an existing definition/super class of the given class in the knowledge base..
boolean	getSingleSuggestionMode() singleSuggestionMode Use this if you are interested in only one suggestion and your learning problem has many (more than 1000) examples..
boolean	getUseAllConstructor() useAllConstructor specifies whether the universal concept constructor is used in the learning algorithm.
boolean	getUseBooleanDatatypes() useBooleanDatatypes specifies whether boolean datatypes are used in the learning algorothm.
boolean	getUseCardinalityRestrictions() useCardinalityRestrictions specifies whether CardinalityRestrictions is used in the learning algorithm.
boolean	getUseDataHasValueConstructor() useDataHasValueConstructor specifies whether the hasValue constructor is used in the learning algorithm in combination with data properties.
boolean	getUseDoubleDatatypes() useDoubleDatatypes specifies whether double datatypes are used in the learning algorothm.
boolean	getUseExistsConstructor() useExistsConstructor specifies whether the existential concept constructor is used in the learning algorithm.
boolean	getUseHasValueConstructor() useHasValueConstructor specifies whether the hasValue constructor is used in the learning algorithm.
boolean	getUseNegation() useNegation specifies whether negation is used in the learning algorothm.
int	getValueFrequencyThreshold() valueFrequencyThreshold specifies how often an object must occur as value in order to be considered for hasValue restrictions.
boolean	isReinitNecessary() true, if this component needs reinitializsation.
void	setCardinalityLimit(int cardinalityLimit)
void	setFilterDescriptionsFollowingFromKB(boolean filterDescriptionsFollowingFromKB)
void	setInstanceBasedDisjoints(boolean instanceBasedDisjoints)
void	setMaxDepth(int maxDepth)
void	setMaxExecutionTimeInSeconds(int maxExecutionTimeInSeconds)
void	setMaxNrOfResults(int maxNrOfResults)
void	setNoisePercentage(double noisePercentage)
void	setReuseExistingDescription(boolean reuseExistingDescription)
void	setSingleSuggestionMode(boolean singleSuggestionMode)
void	setUseAllConstructor(boolean useAllConstructor)
void	setUseBooleanDatatypes(boolean useBooleanDatatypes)
void	setUseCardinalityRestrictions(boolean useCardinalityRestrictions)
void	setUseDataHasValueConstructor(boolean useDataHasValueConstructor)
void	setUseDoubleDatatypes(boolean useDoubleDatatypes)
void	setUseExistsConstructor(boolean useExistsConstructor)
void	setUseHasValueConstructor(boolean useHasValueConstructor)
void	setUseNegation(boolean useNegation)
void	setValueFrequencyThreshold(int valueFrequencyThreshold)

Methods inherited from class org.dllearner.core.configurators.RefinementOperatorConfigurator

getUseStringDatatypes

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ISLEConfigurator

public ISLEConfigurator(ISLE iSLE)

Parameters:

iSLE - see ISLE

Method Detail

getISLE

public static ISLE getISLE(AbstractLearningProblem learningProblem,
                           AbstractReasonerComponent reasoningService)
                    throws LearningProblemUnsupportedException

Parameters:

reasoningService - see reasoningService

learningProblem - see learningProblem

Returns:

ISLE

Throws:

LearningProblemUnsupportedException - see

getUseAllConstructor

public boolean getUseAllConstructor()

useAllConstructor specifies whether the universal concept constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

Specified by:

getUseAllConstructor in class RefinementOperatorConfigurator

Returns:

boolean

getUseExistsConstructor

public boolean getUseExistsConstructor()

useExistsConstructor specifies whether the existential concept constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

Specified by:

getUseExistsConstructor in class RefinementOperatorConfigurator

Returns:

boolean

getUseHasValueConstructor

public boolean getUseHasValueConstructor()

useHasValueConstructor specifies whether the hasValue constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: false

Overrides:

getUseHasValueConstructor in class RefinementOperatorConfigurator

Returns:

boolean

getUseDataHasValueConstructor

public boolean getUseDataHasValueConstructor()

useDataHasValueConstructor specifies whether the hasValue constructor is used in the learning algorithm in combination with data properties. mandatory: false| reinit necessary: true default value: false

Overrides:

getUseDataHasValueConstructor in class RefinementOperatorConfigurator

Returns:

boolean

getValueFrequencyThreshold

public int getValueFrequencyThreshold()

valueFrequencyThreshold specifies how often an object must occur as value in order to be considered for hasValue restrictions. mandatory: false| reinit necessary: true default value: 3

Overrides:

getValueFrequencyThreshold in class RefinementOperatorConfigurator

Returns:

int

getUseCardinalityRestrictions

public boolean getUseCardinalityRestrictions()

useCardinalityRestrictions specifies whether CardinalityRestrictions is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

Specified by:

getUseCardinalityRestrictions in class RefinementOperatorConfigurator

Returns:

boolean

getCardinalityLimit

public int getCardinalityLimit()

cardinalityLimit Gives the maximum number used in cardinality restrictions.. mandatory: false| reinit necessary: true default value: 5

Overrides:

getCardinalityLimit in class RefinementOperatorConfigurator

Returns:

int

getUseNegation

public boolean getUseNegation()

useNegation specifies whether negation is used in the learning algorothm. mandatory: false| reinit necessary: true default value: false

Specified by:

getUseNegation in class RefinementOperatorConfigurator

Returns:

boolean

getUseBooleanDatatypes

public boolean getUseBooleanDatatypes()

useBooleanDatatypes specifies whether boolean datatypes are used in the learning algorothm. mandatory: false| reinit necessary: true default value: true

Specified by:

getUseBooleanDatatypes in class RefinementOperatorConfigurator

Returns:

boolean

getUseDoubleDatatypes

public boolean getUseDoubleDatatypes()

useDoubleDatatypes specifies whether double datatypes are used in the learning algorothm. mandatory: false| reinit necessary: true default value: true

Overrides:

getUseDoubleDatatypes in class RefinementOperatorConfigurator

Returns:

boolean

getMaxExecutionTimeInSeconds

public int getMaxExecutionTimeInSeconds()

maxExecutionTimeInSeconds algorithm will stop after specified seconds. mandatory: false| reinit necessary: true default value: 10

Returns:

int

getNoisePercentage

public double getNoisePercentage()

noisePercentage the (approximated) percentage of noise within the examples. mandatory: false| reinit necessary: true default value: 0.0

Returns:

double

getMaxDepth

public int getMaxDepth()

maxDepth maximum depth of description. mandatory: false| reinit necessary: true default value: 7

Returns:

int

getMaxNrOfResults

public int getMaxNrOfResults()

maxNrOfResults Sets the maximum number of results one is interested in. (Setting this to a lower value may increase performance as the learning algorithm has to store/evaluate/beautify less descriptions).. mandatory: false| reinit necessary: true default value: 10

Returns:

int

getSingleSuggestionMode

public boolean getSingleSuggestionMode()

singleSuggestionMode Use this if you are interested in only one suggestion and your learning problem has many (more than 1000) examples.. mandatory: false| reinit necessary: true default value: false

Returns:

boolean

getInstanceBasedDisjoints

public boolean getInstanceBasedDisjoints()

instanceBasedDisjoints Specifies whether to use real disjointness checks or instance based ones (no common instances) in the refinement operator.. mandatory: false| reinit necessary: true default value: true

Specified by:

getInstanceBasedDisjoints in class RefinementOperatorConfigurator

Returns:

boolean

getFilterDescriptionsFollowingFromKB

public boolean getFilterDescriptionsFollowingFromKB()

filterDescriptionsFollowingFromKB If true, then the results will not contain suggestions, which already follow logically from the knowledge base. Be careful, since this requires a potentially expensive consistency check for candidate solutions.. mandatory: false| reinit necessary: true default value: false

Returns:

boolean

getReuseExistingDescription

public boolean getReuseExistingDescription()

reuseExistingDescription If true, the algorithm tries to find a good starting point close to an existing definition/super class of the given class in the knowledge base.. mandatory: false| reinit necessary: true default value: false

Returns:

boolean

setUseAllConstructor

public void setUseAllConstructor(boolean useAllConstructor)

Parameters:

useAllConstructor - specifies whether the universal concept constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

setUseExistsConstructor

public void setUseExistsConstructor(boolean useExistsConstructor)

Parameters:

useExistsConstructor - specifies whether the existential concept constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

setUseHasValueConstructor

public void setUseHasValueConstructor(boolean useHasValueConstructor)

Parameters:

useHasValueConstructor - specifies whether the hasValue constructor is used in the learning algorithm. mandatory: false| reinit necessary: true default value: false

setUseDataHasValueConstructor

public void setUseDataHasValueConstructor(boolean useDataHasValueConstructor)

Parameters:

useDataHasValueConstructor - specifies whether the hasValue constructor is used in the learning algorithm in combination with data properties. mandatory: false| reinit necessary: true default value: false

setValueFrequencyThreshold

public void setValueFrequencyThreshold(int valueFrequencyThreshold)

Parameters:

valueFrequencyThreshold - specifies how often an object must occur as value in order to be considered for hasValue restrictions. mandatory: false| reinit necessary: true default value: 3

setUseCardinalityRestrictions

public void setUseCardinalityRestrictions(boolean useCardinalityRestrictions)

Parameters:

useCardinalityRestrictions - specifies whether CardinalityRestrictions is used in the learning algorithm. mandatory: false| reinit necessary: true default value: true

setCardinalityLimit

public void setCardinalityLimit(int cardinalityLimit)

Parameters:

cardinalityLimit - Gives the maximum number used in cardinality restrictions.. mandatory: false| reinit necessary: true default value: 5

setUseNegation

public void setUseNegation(boolean useNegation)

Parameters:

useNegation - specifies whether negation is used in the learning algorothm. mandatory: false| reinit necessary: true default value: false

setUseBooleanDatatypes

public void setUseBooleanDatatypes(boolean useBooleanDatatypes)

Parameters:

useBooleanDatatypes - specifies whether boolean datatypes are used in the learning algorothm. mandatory: false| reinit necessary: true default value: true

setUseDoubleDatatypes

public void setUseDoubleDatatypes(boolean useDoubleDatatypes)

Parameters:

useDoubleDatatypes - specifies whether double datatypes are used in the learning algorothm. mandatory: false| reinit necessary: true default value: true

setMaxExecutionTimeInSeconds

public void setMaxExecutionTimeInSeconds(int maxExecutionTimeInSeconds)

Parameters:

maxExecutionTimeInSeconds - algorithm will stop after specified seconds. mandatory: false| reinit necessary: true default value: 10

setNoisePercentage

public void setNoisePercentage(double noisePercentage)

Parameters:

noisePercentage - the (approximated) percentage of noise within the examples. mandatory: false| reinit necessary: true default value: 0.0

setMaxDepth

public void setMaxDepth(int maxDepth)

Parameters:

maxDepth - maximum depth of description. mandatory: false| reinit necessary: true default value: 7

setMaxNrOfResults

public void setMaxNrOfResults(int maxNrOfResults)

Parameters:

maxNrOfResults - Sets the maximum number of results one is interested in. (Setting this to a lower value may increase performance as the learning algorithm has to store/evaluate/beautify less descriptions).. mandatory: false| reinit necessary: true default value: 10

setSingleSuggestionMode

public void setSingleSuggestionMode(boolean singleSuggestionMode)

Parameters:

singleSuggestionMode - Use this if you are interested in only one suggestion and your learning problem has many (more than 1000) examples.. mandatory: false| reinit necessary: true default value: false

setInstanceBasedDisjoints

public void setInstanceBasedDisjoints(boolean instanceBasedDisjoints)

Parameters:

instanceBasedDisjoints - Specifies whether to use real disjointness checks or instance based ones (no common instances) in the refinement operator.. mandatory: false| reinit necessary: true default value: true

setFilterDescriptionsFollowingFromKB

public void setFilterDescriptionsFollowingFromKB(boolean filterDescriptionsFollowingFromKB)

Parameters:

filterDescriptionsFollowingFromKB - If true, then the results will not contain suggestions, which already follow logically from the knowledge base. Be careful, since this requires a potentially expensive consistency check for candidate solutions.. mandatory: false| reinit necessary: true default value: false

setReuseExistingDescription

public void setReuseExistingDescription(boolean reuseExistingDescription)

Parameters:

reuseExistingDescription - If true, the algorithm tries to find a good starting point close to an existing definition/super class of the given class in the knowledge base.. mandatory: false| reinit necessary: true default value: false

isReinitNecessary

public boolean isReinitNecessary()

true, if this component needs reinitializsation.

Returns:

boolean