### Question:
ClassAsInstanceLearningProblem extends AbstractClassExpressionLearningProblem<ScorePosNeg<OWLClass>> { @Override public double getAccuracyOrTooWeak(OWLClassExpression description, double noise) { return getAccuracyOrTooWeakExact(description, noise); }  @Override void init(); @Override ScorePosNeg<OWLClass> computeScore(OWLClassExpression description, double noise); @Override EvaluatedDescription evaluate(OWLClassExpression description); @Override double getAccuracyOrTooWeak(OWLClassExpression description, double noise); double getAccuracyOrTooWeakExact(OWLClassExpression description, double noise); double getPredAccuracyOrTooWeakExact(OWLClassExpression description, double noise); double getFMeasureOrTooWeakExact(OWLClassExpression description, double noise); void setPositiveExamples(Set<OWLClass> positiveExamples); Set<OWLClass> getPositiveExamples(); void setNegativeExamples(Set<OWLClass> negativeExamples); Set<OWLClass> getNegativeExamples(); double getPercentPerLengthUnit(); void setPercentPerLengthUnit(double percentPerLengthUnit); static void main(String[] args);  }### Answer:
@Test public void testGetAccuracyOrTooWeak() throws Exception { OWLOntologyManager man = OWLManager.createOWLOntologyManager(); OWLDataFactory df = man.getOWLDataFactory(); OWLOntology ontology = man.createOntology(); man.addAxiom(ontology, df.getOWLSubObjectPropertyOfAxiom( df.getOWLObjectProperty(IRI.create("p1")), df.getOWLObjectProperty(IRI.create("p2")))); int n = 10; for(int i = 0; i < n; i++) { man.addAxiom(ontology, df.getOWLDeclarationAxiom(df.getOWLClass(IRI.create("A" + i)))); } int n_p = 5; Set<OWLClass> posExamples = new HashSet<>(); for(int i = 0; i < n_p; i++) { posExamples.add(df.getOWLClass(IRI.create("A" + i))); } int n_t = (int) (0.5 * n_p); OWLObjectProperty p1 = df.getOWLObjectProperty(IRI.create("p1")); OWLObjectProperty p2 = df.getOWLObjectProperty(IRI.create("p2")); for(int i = 0; i < n_t; i++) { man.addAxiom(ontology, df.getOWLSubClassOfAxiom( df.getOWLClass(IRI.create("A" + i)), df.getOWLObjectSomeValuesFrom(Math.random() < 0.5 ? p1 : p2, df.getOWLThing()))); } KnowledgeSource ks = new OWLAPIOntology(ontology); ks.init(); AbstractReasonerComponent reasoner = new OWLAPIReasoner(ks); reasoner.init(); ClassAsInstanceLearningProblem lp = new ClassAsInstanceLearningProblem(); lp.setReasoner(reasoner); lp.setPositiveExamples(posExamples); lp.init(); OWLObjectSomeValuesFrom target = df.getOWLObjectSomeValuesFrom(df.getOWLObjectProperty(IRI.create("p2")), df.getOWLThing()); double accuracy = lp.getAccuracyOrTooWeak(target, 1.0); assertTrue(accuracy == 0.4); }