human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "What do Constructive Learners Really Learn?"):
  Abstract: In constructive induction (CI), the learner's problem representation is modified as a normal part of the learning process. This may be necessary if the initial representation is inadequate or inappropriate. However, the distinction between constructive and non-constructive methods appears to be highly ambiguous. Several conventional definitions of the process of constructive induction appear to include all conceivable learning processes. In this paper I argue that the process of constructive learning should be identified with that of relational learning (i.e., I suggest that

Includes members:
  Member "Rule Induction with CN2: Some Recent Improvements":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Multi-class problems and discretization in ICL Extended abstract")
  Member "ID2-of-3: Constructive Induction of M of-N Concepts for Discriminators in Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Effects of Different Types of New Attribute on Constructive Induction")
  Member "Constructive Induction Using a Non-Greedy Strategy for Feature Selection":
    also connected through other hyperedges:
      (none)
  Member "A Hypothesis-driven Constructive Induction Approach to Expanding Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Evolution of the Topology and the Weights of Neural Networks using Genetic Programming with a")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Theory