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 CONJUNCTIVE TESTS FOR DECISION TREES"):
  Abstract: This paper discusses an approach of constructing new attributes based on decision trees and production rules. It can improve the concepts learned in the form of decision trees by simplifying them and improving their predictive accuracy. In addition, this approach can distinguish relevant primitive attributes from irrelevant primitive attributes.

Includes members:
  Member "Constructing Conjunctions using Systematic Search on Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ID2-of-3: Constructive Induction of M of-N Concepts for Discriminators in Decision Trees")
  Member "Constructing Nominal Xof-N Attributes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Effects of Different Types of New Attribute on Constructive Induction")
  Member "ID2-of-3: Constructive Induction of M of-N Concepts for Discriminators in Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Effects of Different Types of New Attribute on Constructive Induction")
  Member "A BENCHMARK FOR CLASSIFIER LEARNING":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping")
  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")

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