org.dllearner.learningproblems

Class PosNegLPStandard

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.OWLNamedIndividual>>

org.dllearner.learningproblems.PosNegLP

org.dllearner.learningproblems.PosNegLPStandard

All Implemented Interfaces:

Cloneable, Component, LearningProblem

Direct Known Subclasses:

PosNegUndLP

public class PosNegLPStandard
extends PosNegLP
implements Cloneable

The aim of this learning problem is to learn a concept definition such that the positive examples and the negative examples do not follow. It is 2-valued, because we only distinguish between covered and non-covered examples. (A 3-valued problem distinguishes between covered examples, examples covered by the negation of the concept, and all other examples.) The 2-valued learning problem is often more useful for Description Logics due to (the Open World Assumption and) the fact that negative knowledge, e.g. that a person does not have a child, is or cannot be expressed.

Author:

Jens Lehmann

Constructor Summary

Constructors

Constructor and Description
PosNegLPStandard()
PosNegLPStandard(AbstractReasonerComponent reasoningService)
PosNegLPStandard(AbstractReasonerComponent reasoningService, SortedSet<org.semanticweb.owlapi.model.OWLIndividual> positiveExamples, SortedSet<org.semanticweb.owlapi.model.OWLIndividual> negativeExamples)
PosNegLPStandard(PosNegLP lp) Copy constructor

Method Summary

Modifier and Type	Method and Description
Object	clone()
ScorePosNeg	computeScore(org.semanticweb.owlapi.model.OWLClassExpression concept, double noise) Computes score of a given concept using the reasoner.
EvaluatedDescription	evaluate(org.semanticweb.owlapi.model.OWLClassExpression description, double noise) 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.
void	init() Method to be called after the component has been configured.

Methods inherited from class org.dllearner.learningproblems.PosNegLP

getAccuracyMethod, getNegativeExamples, getPercentPerLengthUnit, getPositiveExamples, isUseRetrievalForClassification, setAccuracyMethod, setNegativeExamples, setPercentPerLengthUnit, setPositiveExamples, setUseRetrievalForClassification

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

PosNegLPStandard

public PosNegLPStandard()

PosNegLPStandard

public PosNegLPStandard(AbstractReasonerComponent reasoningService)

PosNegLPStandard

public PosNegLPStandard(PosNegLP lp)

Copy constructor

Parameters:

lp - the learning problem

PosNegLPStandard

public PosNegLPStandard(AbstractReasonerComponent reasoningService,
                        SortedSet<org.semanticweb.owlapi.model.OWLIndividual> positiveExamples,
                        SortedSet<org.semanticweb.owlapi.model.OWLIndividual> negativeExamples)

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.

Specified by:

init in interface Component

Overrides:

init in class PosNegLP

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 computeScore(org.semanticweb.owlapi.model.OWLClassExpression concept,
                                double noise)

Computes score of a given concept using the reasoner.

Specified by:

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

Parameters:

concept - The concept to test.

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

Returns:

Corresponding Score object.

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.OWLNamedIndividual>,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<ScorePosNeg<org.semanticweb.owlapi.model.OWLNamedIndividual>>>

Returns:

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

evaluate

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

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.OWLNamedIndividual>,org.semanticweb.owlapi.model.OWLClassExpression,EvaluatedDescription<ScorePosNeg<org.semanticweb.owlapi.model.OWLNamedIndividual>>>

Parameters:

description - Hypothesis to evaluate.

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

Returns:

an evaluated hypothesis

clone

public Object clone()
             throws CloneNotSupportedException

Overrides:

clone in class Object

Throws:

CloneNotSupportedException