Method NumPredictOneRow

src/boosting/gbdt.h:213–226

! * \brief Get number of prediction for one data * \param num_iteration number of used iterations * \param is_pred_leaf True if predicting leaf index * \param is_pred_contrib True if predicting feature contribution * \return number of prediction */

  * \return number of prediction
  */
  inline int NumPredictOneRow(int num_iteration, bool is_pred_leaf, bool is_pred_contrib) const override {
    int num_preb_in_one_row = num_class_ * num_labels_;
    if (is_pred_leaf) {
      int max_iteration = GetCurrentIteration();
      if (num_iteration > 0) {
        num_preb_in_one_row *= static_cast<int>(std::min(max_iteration, num_iteration));
      } else {
        num_preb_in_one_row *= max_iteration;
      }
    } else if (is_pred_contrib) {
      num_preb_in_one_row = num_tree_per_iteration_ * (max_feature_idx_ + 2);  // +1 for 0-based indexing, +1 for baseline
    }
    return num_preb_in_one_row;
  }

  void PredictRaw(const double* features, double* output,
                  const PredictionEarlyStopInstance* earlyStop) const override;