org.dllearner.learningproblems

Class ClassAsInstanceLearningProblem

java.lang.Object

org.dllearner.core.AbstractComponent

org.dllearner.core.AbstractLearningProblem<T,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<T>>

org.dllearner.core.AbstractClassExpressionLearningProblem<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>>

org.dllearner.learningproblems.ClassAsInstanceLearningProblem

All Implemented Interfaces:

Component, LearningProblem

public class ClassAsInstanceLearningProblem
extends AbstractClassExpressionLearningProblem<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>>

A learning problem in which positive and negative examples are classes, i.e. the whole learning is done on the schema level. Instead of doing instance checks to compute the quality of a given class expression, we check for subclass relationship.

Author:

Lorenz Buehmann

Constructor Summary

Constructors

Constructor and Description
ClassAsInstanceLearningProblem()

Method Summary

Modifier and Type	Method and Description
ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>	computeScore(org.semanticweb.owlapi.model.OWLClassExpression description, double noise) Computes the Score of a given hypothesis with respect to this learning problem.
EvaluatedDescription	evaluate(org.semanticweb.owlapi.model.OWLClassExpression description) Evaluates the hypothesis by computing the score and returning an evaluated hypothesis of the correct type (ClassLearningProblem returns EvaluatedDescriptionClass instead of generic EvaluatedDescription).
double	getAccuracyOrTooWeak(org.semanticweb.owlapi.model.OWLClassExpression description, double noise) This method computes the accuracy and returns -1 instead of the accuracy if the accuracy of the hypothesis is below the given threshold and the accuracy of all more special w.r.t.
double	getAccuracyOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description, double noise)
double	getFMeasureOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description, double noise)
Set<org.semanticweb.owlapi.model.OWLClass>	getNegativeExamples()
double	getPercentPerLengthUnit()
Set<org.semanticweb.owlapi.model.OWLClass>	getPositiveExamples()
double	getPredAccuracyOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description, double noise)
void	init() Method to be called after the component has been configured.
static void	main(String[] args)
void	setNegativeExamples(Set<org.semanticweb.owlapi.model.OWLClass> negativeExamples)
void	setPercentPerLengthUnit(double percentPerLengthUnit)
void	setPositiveExamples(Set<org.semanticweb.owlapi.model.OWLClass> positiveExamples)

Methods inherited from class org.dllearner.core.AbstractClassExpressionLearningProblem

changeReasonerComponent, getExampleLoaderHelper, getReasoningUtil, setExampleLoaderHelper, setReasoner, setReasoningUtil

Methods inherited from class org.dllearner.core.AbstractLearningProblem

computeScore, evaluate, getAccuracyOrTooWeak, getReasoner

Methods inherited from class org.dllearner.core.AbstractComponent

isInitialized

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassAsInstanceLearningProblem

public ClassAsInstanceLearningProblem()

Method Detail

init

public void init()
          throws ComponentInitException

Description copied from interface: Component

Method to be called after the component has been configured. Implementation of components can overwrite this method to perform setup and initialisation tasks for this component.

Throws:

ComponentInitException - This exception is thrown if any exceptions occur within the initialisation process of this component. As component developer, you are encouraged to re-throw occurring exception as ComponentInitException and giving an error message as well as the actually exception by using the constructor ComponentInitException(String, Throwable).

computeScore

public ScorePosNeg<org.semanticweb.owlapi.model.OWLClass> computeScore(org.semanticweb.owlapi.model.OWLClassExpression description,
                                                                       double noise)

Description copied from class: AbstractLearningProblem

Computes the Score of a given hypothesis with respect to this learning problem. This can (but does not need to) be used by learning algorithms to measure how good the hypothesis fits the learning problem. Score objects are used to store e.g. covered examples, accuracy etc., so often it is more efficient to only create score objects for promising hypotheses.

Specified by:

computeScore in class AbstractLearningProblem<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>>>

Parameters:

description - A hypothesis (as solution candidate for this learning problem).

noise - the (approximated) value of noise within the examples

Returns:

A Score object.

evaluate

public EvaluatedDescription evaluate(org.semanticweb.owlapi.model.OWLClassExpression description)

Description copied from class: AbstractLearningProblem

Evaluates the hypothesis by computing the score and returning an evaluated hypothesis of the correct type (ClassLearningProblem returns EvaluatedDescriptionClass instead of generic EvaluatedDescription).

Overrides:

evaluate in class AbstractLearningProblem<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>>>

Parameters:

description - Hypothesis to evaluate.

Returns:

an evaluated hypothesis

getAccuracyOrTooWeak

public double getAccuracyOrTooWeak(org.semanticweb.owlapi.model.OWLClassExpression description,
                                   double noise)

Description copied from class: AbstractLearningProblem

This method computes the accuracy and returns -1 instead of the accuracy if

1. the accuracy of the hypothesis is below the given threshold and
2. the accuracy of all more special w.r.t. subsumption hypotheses is below the given threshold.

This is used for efficiency reasons, i.e. -1 can be returned instantly if it is clear that the hypothesis and all its refinements are not sufficiently accurate.

Specified by:

getAccuracyOrTooWeak in class AbstractLearningProblem<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<ScorePosNeg<org.semanticweb.owlapi.model.OWLClass>>>

Returns:

A value between 0 and 1 indicating the quality (of a hypothesis) or -1 as described above.

getAccuracyOrTooWeakExact

public double getAccuracyOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description,
                                        double noise)

getPredAccuracyOrTooWeakExact

public double getPredAccuracyOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description,
                                            double noise)

getFMeasureOrTooWeakExact

public double getFMeasureOrTooWeakExact(org.semanticweb.owlapi.model.OWLClassExpression description,
                                        double noise)

setPositiveExamples

public void setPositiveExamples(Set<org.semanticweb.owlapi.model.OWLClass> positiveExamples)

Parameters:

positiveExamples - the positiveExamples to set

getPositiveExamples

public Set<org.semanticweb.owlapi.model.OWLClass> getPositiveExamples()

Returns:

the positiveExamples

setNegativeExamples

public void setNegativeExamples(Set<org.semanticweb.owlapi.model.OWLClass> negativeExamples)

Parameters:

negativeExamples - the negativeExamples to set

getNegativeExamples

public Set<org.semanticweb.owlapi.model.OWLClass> getNegativeExamples()

Returns:

the negativeExamples

getPercentPerLengthUnit

public double getPercentPerLengthUnit()

Returns:

the percentPerLengthUnit

setPercentPerLengthUnit

public void setPercentPerLengthUnit(double percentPerLengthUnit)

Parameters:

percentPerLengthUnit - the percentPerLengthUnit to set

main

public static void main(String[] args)
                 throws Exception

Throws:

Exception