anchor.diff:          [17, 10, 32, 3],
           [70, 80, 90, 3],
         ]);
  -      final outcomesColumnRange = ZRange.singleton(3);
   
         final classLabel = 3.0;
         final classProbability = 1.0;
  
positive.code:         classLabel: classProbability,
        });
  
        final distributionCalculator = createDistributionCalculator<double>(
          observations.getColumn(3),
          distribution,
        );
        final labelFactory = MajorityLeafLabelFactory(distributionCalculator);
        final label = labelFactory.create(observations, outcomesColumnRange,
            false);
  
        expect(label.numericalValue, equals(classLabel));
        expect(label.nominalValue, isNull);
  
negative.code:   });
  }
  
  SequenceElementsDistributionCalculator createDistributionCalculator(
      Iterable<num> values, HashMap<double, double> distribution) {
    final distributionCalculator = DistributionCalculatorMock();
  
    when(distributionCalculator.calculate<double>(argThat(equals(values)), any))
        .thenReturn(distribution);
  
    return distributionCalculator;
  