code: @Override protected double score1( Chunk chks[], double weight, double offset, double fs[/*nclass*/], int row ) {
      double sum = 0;
      if (_nclass > 2 || (_nclass == 2 && !_model.binomialOpt())) {
        for (int k = 0; k < _nclass; k++)
          sum += (fs[k+1] = weight * chk_tree(chks, k).atd(row) / chk_oobt(chks).atd(row));
      }
      else if (_nclass==2 && _model.binomialOpt()) {
        fs[1] = weight * chk_tree(chks, 0).atd(row) / chk_oobt(chks).atd(row);
        if (fs[1]>1 && fs[1]<=ONEBOUND)
          fs[1] = 1.0;
        else if (fs[1]<0 && fs[1]>=ZEROBOUND)
          fs[1] = 0.0;
        assert(fs[1] >= 0 && fs[1] <= 1);
        fs[2] = 1. - fs[1];
      }
      else { //regression
        // average per trees voted for this row (only trees which have row in "out-of-bag"
        sum += (fs[0] = weight * chk_tree(chks, 0).atd(row) / chk_oobt(chks).atd(row) );
        fs[1] = 0;
      }
      return sum;
    }
  
  
  }
docs: turns the results into a probability distribution.