org.dllearner.core.configurators
Class FuzzyPosNegLPStandardConfigurator

java.lang.Object
  extended by org.dllearner.core.configurators.FuzzyPosNegLPStandardConfigurator
All Implemented Interfaces:
Configurator

public class FuzzyPosNegLPStandardConfigurator
extends Object
implements Configurator

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


Constructor Summary
FuzzyPosNegLPStandardConfigurator(FuzzyPosNegLPStandard fuzzyPosNegLPStandard)
           
 
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<Object> getFuzzyExamples()
          fuzzyExamples fuzzy examples.
static FuzzyPosNegLPStandard getFuzzyPosNegLPStandard(AbstractReasonerComponent reasoningService, Set<Object> fuzzyExamples, Set<String> positiveExamples, Set<String> negativeExamples)
           
 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.
 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 setFuzzyExamples(Set<Object> fuzzyExamples)
           
 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

FuzzyPosNegLPStandardConfigurator

public FuzzyPosNegLPStandardConfigurator(FuzzyPosNegLPStandard fuzzyPosNegLPStandard)
Parameters:
fuzzyPosNegLPStandard - see FuzzyPosNegLPStandard
Method Detail

getFuzzyPosNegLPStandard

public static FuzzyPosNegLPStandard getFuzzyPosNegLPStandard(AbstractReasonerComponent reasoningService,
                                                             Set<Object> fuzzyExamples,
                                                             Set<String> positiveExamples,
                                                             Set<String> negativeExamples)
Parameters:
reasoningService - see reasoningService
fuzzyExamples - fuzzy examples
positiveExamples - positive examples
negativeExamples - negative examples
Returns:
FuzzyPosNegLPStandard

getFuzzyExamples

public Set<Object> getFuzzyExamples()
fuzzyExamples fuzzy examples. mandatory: true| reinit necessary: false default value: null

Returns:
Set(Object)

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

setFuzzyExamples

public void setFuzzyExamples(Set<Object> fuzzyExamples)
Parameters:
fuzzyExamples - fuzzy examples. mandatory: true| reinit necessary: false default value: null

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


SourceForge.net Logo DL-Learner is licenced under the terms of the GNU General Public License.
Copyright © 2007-2011 Jens Lehmann