docs: private Instance generateMLInstance(HashSet<Integer> Y) {
  
          // create a multi-label instance:
          Instance x_ml = new SparseInstance(this.multilabelStreamTemplate.numAttributes());
          x_ml.setDataset(this.multilabelStreamTemplate);
  
          // set classes
          for (int j = 0; j < m_L; j++) {
              x_ml.setValue(j, 0.0);
          }
          for (int l : Y) {
              x_ml.setValue(l, 1.0);
          }
  
          // generate binary instances
          Instance x_0 = getNextWithBinary(0);
          Instance x_1 = getNextWithBinary(1);
  
          // Loop through each feature attribute @warning: assumes class is last index
          for (int a = 0; a < m_A; a++) {
  
              // The combination is present: use a positive value
              if (Y.containsAll(m_TopCombinations[a])) {
                  x_ml.setValue(m_L + a, x_1.value(a));
                  //x_ml.setValue(m_L+a,1.0);
              } // The combination is absent: use a negative value
              else {
                  x_ml.setValue(m_L + a, x_0.value(a));
                  //x_ml.setValue(m_L+a,0.0);
              }
          }
  
          return x_ml;
      }