double pred;
Instance classMissing = (Instance)instance.copy(); double pred = 0; classMissing.setDataset(instance.dataset()); classMissing.setClassMissing();
  public double evaluateModelOnce(double [] dist, 				  Instance instance) throws Exception {    double pred;    if (m_ClassIsNominal) {      pred = Utils.maxIndex(dist);      if (dist[(int)pred] <= 0) {	pred = Instance.missingValue();      }      updateStatsForClassifier(dist, instance);    } else {      pred = dist[0];      updateStatsForPredictor(pred, instance);    }    return pred;  }