org.dllearner.core
Interface AxiomLearningAlgorithm

All Superinterfaces:
Component, LearningAlgorithm
All Known Implementing Classes:
AbstractAxiomLearningAlgorithm, DataPropertyDomainAxiomLearner, DataPropertyRangeAxiomLearner, DisjointClassesLearner, DisjointDataPropertyAxiomLearner, DisjointObjectPropertyAxiomLearner, EquivalentDataPropertyAxiomLearner, EquivalentObjectPropertyAxiomLearner, FunctionalDataPropertyAxiomLearner, FunctionalObjectPropertyAxiomLearner, InverseFunctionalObjectPropertyAxiomLearner, IrreflexiveObjectPropertyAxiomLearner, ObjectPropertyDomainAxiomLearner, ObjectPropertyRangeAxiomLearner, ReflexiveObjectPropertyAxiomLearner, SimpleSubclassLearner, SubDataPropertyOfAxiomLearner, SubObjectPropertyOfAxiomLearner, SymmetricObjectPropertyAxiomLearner, TransitiveObjectPropertyAxiomLearner

public interface AxiomLearningAlgorithm
extends LearningAlgorithm


Method Summary
 List<Axiom> getCurrentlyBestAxioms()
           
 List<Axiom> getCurrentlyBestAxioms(int nrOfAxioms)
           
 List<EvaluatedAxiom> getCurrentlyBestEvaluatedAxioms()
           
 List<EvaluatedAxiom> getCurrentlyBestEvaluatedAxioms(int nrOfAxioms)
           
 
Methods inherited from interface org.dllearner.core.LearningAlgorithm
start
 
Methods inherited from interface org.dllearner.core.Component
init
 

Method Detail

getCurrentlyBestAxioms

List<Axiom> getCurrentlyBestAxioms()
Returns:
The best axioms found by the learning algorithm so far.

getCurrentlyBestAxioms

List<Axiom> getCurrentlyBestAxioms(int nrOfAxioms)
Parameters:
nrOfAxioms - Limit for the number or returned axioms.
Returns:
The best axioms found by the learning algorithm so far.

getCurrentlyBestEvaluatedAxioms

List<EvaluatedAxiom> getCurrentlyBestEvaluatedAxioms()
Returns:
The best evaluated axioms found by the learning algorithm so far.

getCurrentlyBestEvaluatedAxioms

List<EvaluatedAxiom> getCurrentlyBestEvaluatedAxioms(int nrOfAxioms)
Parameters:
nrOfAxioms - Limit for the number or returned evaluated axioms.
Returns:
The best evaluated axioms found by the learning algorithm so far.


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Copyright © 2007-2011 Jens Lehmann