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 "Constructive Induction Using a Non-Greedy Strategy for Feature Selection"):
  Abstract: We present a method for feature construction and selection that finds a minimal set of conjunctive features that are appropriate to perform the classification task. For problems where this bias is appropriate, the method outperforms other constructive induction algorithms and is able to achieve higher classification accuracy. The application of the method in the search for minimal multi-level boolean expressions is presented and analyzed with the help of some examples.

Includes members:
  Member "What do Constructive Learners Really Learn?":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Rule Induction with CN2: Some Recent Improvements")
  Member "Unsupervised Constructive Learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Rule Induction with CN2: Some Recent Improvements")

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