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 "First Order Regression"):
  Abstract: We present a new approach, called First Order Regression (FOR), to handling numerical information in Inductive Logic Programming (ILP). FOR is a combination of ILP and numerical regression. First-order logic descriptions are induced to carve out those subspaces that are amenable to numerical regression among real-valued variables. The program Fors is an implementation of this idea, where numerical regression is focused on a distinguished continuous argument of the target predicate. We show that this can be viewed as a generalisation of the usual ILP problem. Applications of Fors on several real-world data sets are described: the prediction of mutagenicity of chemicals, the modelling of liquid dynamics in a surge tank, predicting the roughness in steel grinding, finite element mesh design, and operator's skill reconstruction in electric discharge machining. A comparison of Fors' performance with previous results in these domains indicates that Fors is an effective tool for ILP applications that involve numerical data.

Includes members:
  Member "Employing Linear Regression in Regression Tree Leaves":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Structural Regression Trees")
  Member "Producing More Comprehensible Models While Retaining Their Performance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "First Order Regression: Applications in Real-World Domains")
  Member "First Order Regression: Applications in Real-World Domains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Producing More Comprehensible Models While Retaining Their Performance")

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: Rule_Learning