pred = Utils.maxIndex(dist); if (dist[(int)pred] <= 0) { pred = Instance.missingValue(); } updateStatsForClassifier(dist, instance);
double [] dist = classifier.distributionForInstance(classMissing); pred = Utils.maxIndex(dist); if (dist[(int)pred] <= 0) { pred = Instance.missingValue(); } updateStatsForClassifier(dist, instance);
  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;  }