Esempio n. 1
0
  /**
   * Calculates the class membership probabilities for the given test instance.
   *
   * @param instance the instance to be classified
   * @return predicted class probability distribution
   * @exception Exception if distribution can't be computed successfully
   */
  public double[] distributionForInstance(Instance instance) throws Exception {
    if (instance.classAttribute().isNumeric()) {
      throw new UnsupportedClassTypeException("Decorate can't handle a numeric class!");
    }
    double[] sums = new double[instance.numClasses()], newProbs;
    Classifier curr;

    for (int i = 0; i < m_Committee.size(); i++) {
      curr = (Classifier) m_Committee.get(i);
      newProbs = curr.distributionForInstance(instance);
      for (int j = 0; j < newProbs.length; j++) sums[j] += newProbs[j];
    }
    if (Utils.eq(Utils.sum(sums), 0)) {
      return sums;
    } else {
      Utils.normalize(sums);
      return sums;
    }
  }
Esempio n. 2
0
 /**
  * Calculates the class membership probabilities for the given test instance.
  *
  * @param instance the instance to be classified
  * @return predicted class probability distribution
  * @throws Exception if class is numeric
  */
 public double[] distributionForInstance(Instance instance) throws Exception {
   if (m_GroovyObject != null) return m_GroovyObject.distributionForInstance(instance);
   else return new double[instance.numClasses()];
 }