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 "Constructing Nominal Xof-N Attributes"):
  Abstract: Most constructive induction researchers focus only on new boolean attributes. This paper reports a new constructive induction algorithm, called XofN, that constructs new nominal attributes in the form of Xof-N representations. An Xof-N is a set containing one or more attribute-value pairs. For a given instance, its value corresponds to the number of its attribute-value pairs that are true. The promising preliminary experimental results, on both artificial and real-world domains, show that constructing new nominal attributes in the form of Xof-N representations can significantly improve the performance of selective induction in terms of both higher prediction accuracy and lower theory complexity.

Includes members:
  Member "Multivariate versus Univariate Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Multivariate Decision Trees")
  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 "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Effects of Different Types of New Attribute on Constructive Induction")
  Member "CONSTRUCTING CONJUNCTIVE TESTS FOR DECISION TREES":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Continuous-valued Xof-N Attributes Versus Nominal Xof-N Attributes for Constructive Induction: A Case Study")
  Member "Continuous-valued Xof-N Attributes Versus Nominal Xof-N Attributes for Constructive Induction: A Case Study":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Effects of Different Types of New Attribute on Constructive Induction")
  Member "Effects of Different Types of New Attribute on Constructive Induction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Continuous-valued Xof-N Attributes Versus Nominal Xof-N Attributes for Constructive Induction: A Case Study")

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