code: def build(cls, data, *args, **kwargs):
          
          assert isinstance(data, Data)
          if data.is_continuous_class:
              fitness_func = gain_variance
          else:
              fitness_func = get_gain
          
          t = cls(data=data, *args, **kwargs)
          t._data = data
          t.sample_count = len(data)
          t._tree = create_decision_tree(
              data=data,
              attributes=data.attribute_names,
              class_attr=data.class_attribute_name,
              fitness_func=fitness_func,
              wrapper=t,
          )
          return t
docs: Constructs a classification or regression tree in a single batch by
          analyzing the given data.