@Override public ValueType getFirst() { return this.getValue(); }
@Override public ValueType getFirst() { return this.getValue(); }
@Override public ValueType getFirst() { return this.getValue(); }
@Override public CategoryType evaluate( final Vectorizable input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final Vectorizable input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final ObservationType input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final Collection<InputType> inputs ) { return this.evaluateWithDiscriminant(inputs).getValue(); }
@Override public CategoryType evaluate( final ObservationType input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final ObservationType input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final Vectorizable input) { return this.evaluateWithDiscriminant(input).getValue(); }
@Override public CategoryType evaluate( final Collection<InputType> inputs ) { return this.evaluateWithDiscriminant(inputs).getValue(); }
@Override public CategoryType evaluate( final Collection<InputType> inputs ) { return this.evaluateWithDiscriminant(inputs).getValue(); }
@Override protected <ANNOTATION> List<ScoredAnnotation<ANNOTATION>> getAnnotations(VectorNaiveBayesCategorizer<ANNOTATION, PDF> categorizer, Vector vec) { final List<ScoredAnnotation<ANNOTATION>> results = new ArrayList<ScoredAnnotation<ANNOTATION>>(); final DefaultWeightedValueDiscriminant<ANNOTATION> r = categorizer.evaluateWithDiscriminant(vec); results.add(new ScoredAnnotation<ANNOTATION>(r.getValue(), (float) Math.exp(r.getWeight()))); return results; } };