How to use

DefaultWeightedValueDiscriminant

in

gov.sandia.cognition.learning.data

@Override
public ValueType getFirst()
{
  return this.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;
  }
};

/**
 * Convenience method for creating a new
 * {@code DefaultWeightedValueDiscriminant} with the given value and weight.
 *
 * @param   <ValueType>
 *      The type of value to discriminate between.
 * @param   value
 *      The value for the pair.
 * @param   weight
 *      The weight that is to be used as the discriminant.
 * @return
 *      A new discriminant object.
 */
public static <ValueType> DefaultWeightedValueDiscriminant<ValueType> create(
  final ValueType value,
  final double weight)
{
  return new DefaultWeightedValueDiscriminant<ValueType>(value, weight);
}

  new DefaultWeightedValueDiscriminant<CategoryType>();
result.setValue(minCat);
result.setWeight(minDelta);

@Override
public ValueDiscriminantPair<Boolean, Double> evaluateWithDiscriminant(
  final InputType input)
{
  // Evaluate the input as a double whose sign is the category.
  final double value = this.evaluateAsDouble(input);
  final boolean category = value >= 0.0;
  // The discriminant needs to be larger for a better match, even in
  // the case of the false category, which requires doing an absolute
  // value to the sign.
  final double discriminant = category ? value : -value;
  return DefaultWeightedValueDiscriminant.create(category, discriminant);
}

@Override
public Double getDiscriminant()
{
  return this.getWeight();
}

  new DefaultWeightedValueDiscriminant<CategoryType>();
result.setValue(minCat);
result.setWeight(minDelta);

@Override
public ValueDiscriminantPair<Boolean, Double> evaluateWithDiscriminant(
  final InputType input)
{
  // Evaluate the input as a double whose sign is the category.
  final double value = this.evaluateAsDouble(input);
  final boolean category = value >= 0.0;
  // The discriminant needs to be larger for a better match, even in
  // the case of the false category, which requires doing an absolute
  // value to the sign.
  final double discriminant = category ? value : -value;
  return DefaultWeightedValueDiscriminant.create(category, discriminant);
}

@Override
public Double getSecond()
{
  return this.getWeight();
}

  new DefaultWeightedValueDiscriminant<CategoryType>();
result.setValue(minCat);
result.setWeight(minDelta);

@Override
public ValueType getFirst()
{
  return this.getValue();
}

@Override
public ValueDiscriminantPair<Boolean, Double> evaluateWithDiscriminant(
  final InputType input)
{
  // Evaluate the input as a double whose sign is the category.
  final double value = this.evaluateAsDouble(input);
  final boolean category = value >= 0.0;
  // The discriminant needs to be larger for a better match, even in
  // the case of the false category, which requires doing an absolute
  // value to the sign.
  final double discriminant = category ? value : -value;
  return DefaultWeightedValueDiscriminant.create(category, discriminant);
}

@Override
public Double getSecond()
{
  return this.getWeight();
}

/**
 * Convenience method for creating a new
 * {@code DefaultWeightedValueDiscriminant} with the given value and weight.
 *
 * @param   <ValueType>
 *      The type of value to discriminate between.
 * @param   value
 *      The value for the pair.
 * @param   weight
 *      The weight that is to be used as the discriminant.
 * @return
 *      A new discriminant object.
 */
public static <ValueType> DefaultWeightedValueDiscriminant<ValueType> create(
  final ValueType value,
  final double weight)
{
  return new DefaultWeightedValueDiscriminant<ValueType>(value, weight);
}

  new DefaultWeightedValueDiscriminant<CategoryType>();
result.setValue(minCat);
result.setWeight(minDelta);

@Override
public ValueType getFirst()
{
  return this.getValue();
}

@Override
public DefaultWeightedValueDiscriminant<CategoryType> evaluateWithDiscriminant(
  final ObservationType input)
{
  CategoryType maxCategory = null;
  double maxPosterior = Double.NEGATIVE_INFINITY;
  for( CategoryType category : this.getCategories() )
  {
    double posterior = this.computePosterior(input, category);
    if( maxPosterior < posterior )
    {
      maxPosterior = posterior;
      maxCategory = category;
    }
  }
  return DefaultWeightedValueDiscriminant.create(maxCategory, maxPosterior);
}

@Override
public Double getDiscriminant()
{
  return this.getWeight();
}

/**
 * Convenience method for creating a new
 * {@code DefaultWeightedValueDiscriminant} with the given value and weight.
 *
 * @param   <ValueType>
 *      The type of value to discriminate between.
 * @param   value
 *      The value for the pair.
 * @param   weight
 *      The weight that is to be used as the discriminant.
 * @return
 *      A new discriminant object.
 */
public static <ValueType> DefaultWeightedValueDiscriminant<ValueType> create(
  final ValueType value,
  final double weight)
{
  return new DefaultWeightedValueDiscriminant<ValueType>(value, weight);
}

  new DefaultWeightedValueDiscriminant<CategoryType>();
result.setValue(minCat);
result.setWeight(minDelta);