org.dllearner.core.configurators
Class PosNegLPStandardConfigurator

java.lang.Object
  org.dllearner.core.configurators.PosNegLPStandardConfigurator

All Implemented Interfaces:

Configurator

public class PosNegLPStandardConfigurator
extends Object
implements Configurator

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

Constructor Summary

PosNegLPStandardConfigurator(PosNegLPStandard posNegLPStandard)

Method Summary

String	getAccuracyMethod() accuracyMethod Specifies, which method/function to use for computing accuracy..
double	getApproxAccuracy() approxAccuracy accuracy of the approximation (only for expert use).
Set<String>	getNegativeExamples() negativeExamples negative examples.
double	getPercentPerLenghtUnit() percentPerLenghtUnit describes the reduction in classification accuracy in percent one is willing to accept for reducing the length of the concept by one.
Set<String>	getPositiveExamples() positiveExamples positive examples.
static PosNegLPStandard	getPosNegLPStandard(AbstractReasonerComponent reasoningService, Set<String> positiveExamples, Set<String> negativeExamples)
boolean	getUseApproximations() useApproximations whether to use stochastic approximations for computing accuracy.
String	getUseMultiInstanceChecks() useMultiInstanceChecks See UseMultiInstanceChecks enum. - NO LONGER FULLY SUPPORTED..
boolean	getUseRetrievalForClassficiation() useRetrievalForClassficiation Specifies whether to use retrieval or instance checks for testing a concept. - NO LONGER FULLY SUPPORTED..
boolean	isReinitNecessary() true, if this component needs reinitializsation.
void	setAccuracyMethod(String accuracyMethod)
void	setApproxAccuracy(double approxAccuracy)
void	setNegativeExamples(Set<String> negativeExamples)
void	setPercentPerLenghtUnit(double percentPerLenghtUnit)
void	setPositiveExamples(Set<String> positiveExamples)
void	setUseApproximations(boolean useApproximations)
void	setUseMultiInstanceChecks(String useMultiInstanceChecks)
void	setUseRetrievalForClassficiation(boolean useRetrievalForClassficiation)

Methods inherited from class java.lang.Object

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

Constructor Detail

PosNegLPStandardConfigurator

public PosNegLPStandardConfigurator(PosNegLPStandard posNegLPStandard)

Parameters:

posNegLPStandard - see PosNegLPStandard

Method Detail

getPosNegLPStandard

public static PosNegLPStandard getPosNegLPStandard(AbstractReasonerComponent reasoningService,
                                                   Set<String> positiveExamples,
                                                   Set<String> negativeExamples)

Parameters:

reasoningService - see reasoningService

positiveExamples - positive examples

negativeExamples - negative examples

Returns:

PosNegLPStandard

getPositiveExamples

public Set<String> getPositiveExamples()

positiveExamples positive examples. mandatory: true| reinit necessary: false default value: null

Returns:

Set(String)

getNegativeExamples

public Set<String> getNegativeExamples()

negativeExamples negative examples. mandatory: true| reinit necessary: false default value: null

Returns:

Set(String)

getUseRetrievalForClassficiation

public boolean getUseRetrievalForClassficiation()

useRetrievalForClassficiation Specifies whether to use retrieval or instance checks for testing a concept. - NO LONGER FULLY SUPPORTED.. mandatory: false| reinit necessary: true default value: false

Returns:

boolean

getPercentPerLenghtUnit

public double getPercentPerLenghtUnit()

percentPerLenghtUnit describes the reduction in classification accuracy in percent one is willing to accept for reducing the length of the concept by one. mandatory: false| reinit necessary: true default value: 0.05

Returns:

double

getUseMultiInstanceChecks

public String getUseMultiInstanceChecks()

useMultiInstanceChecks See UseMultiInstanceChecks enum. - NO LONGER FULLY SUPPORTED.. mandatory: false| reinit necessary: true default value: twoChecks

Returns:

String

getUseApproximations

public boolean getUseApproximations()

useApproximations whether to use stochastic approximations for computing accuracy. mandatory: false| reinit necessary: true default value: false

Returns:

boolean

getApproxAccuracy

public double getApproxAccuracy()

approxAccuracy accuracy of the approximation (only for expert use). mandatory: false| reinit necessary: true default value: 0.05

Returns:

double

getAccuracyMethod

public String getAccuracyMethod()

accuracyMethod Specifies, which method/function to use for computing accuracy.. mandatory: false| reinit necessary: true default value: predacc

Returns:

String

setPositiveExamples

public void setPositiveExamples(Set<String> positiveExamples)

Parameters:

positiveExamples - positive examples. mandatory: true| reinit necessary: false default value: null

setNegativeExamples

public void setNegativeExamples(Set<String> negativeExamples)

Parameters:

negativeExamples - negative examples. mandatory: true| reinit necessary: false default value: null

setUseRetrievalForClassficiation

public void setUseRetrievalForClassficiation(boolean useRetrievalForClassficiation)

Parameters:

useRetrievalForClassficiation - Specifies whether to use retrieval or instance checks for testing a concept. - NO LONGER FULLY SUPPORTED.. mandatory: false| reinit necessary: true default value: false

setPercentPerLenghtUnit

public void setPercentPerLenghtUnit(double percentPerLenghtUnit)

Parameters:

percentPerLenghtUnit - describes the reduction in classification accuracy in percent one is willing to accept for reducing the length of the concept by one. mandatory: false| reinit necessary: true default value: 0.05

setUseMultiInstanceChecks

public void setUseMultiInstanceChecks(String useMultiInstanceChecks)

Parameters:

useMultiInstanceChecks - See UseMultiInstanceChecks enum. - NO LONGER FULLY SUPPORTED.. mandatory: false| reinit necessary: true default value: twoChecks

setUseApproximations

public void setUseApproximations(boolean useApproximations)

Parameters:

useApproximations - whether to use stochastic approximations for computing accuracy. mandatory: false| reinit necessary: true default value: false

setApproxAccuracy

public void setApproxAccuracy(double approxAccuracy)

Parameters:

approxAccuracy - accuracy of the approximation (only for expert use). mandatory: false| reinit necessary: true default value: 0.05

setAccuracyMethod

public void setAccuracyMethod(String accuracyMethod)

Parameters:

accuracyMethod - Specifies, which method/function to use for computing accuracy.. mandatory: false| reinit necessary: true default value: predacc

isReinitNecessary

public boolean isReinitNecessary()

true, if this component needs reinitializsation.

Returns:

boolean