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 "Using Qualitative Models to Guide Inductive Learning"):
  Abstract: This paper presents a method for using qualitative models to guide inductive learning. Our objectives are to induce rules which are not only accurate but also explainable with respect to the qualitative model, and to reduce learning time by exploiting domain knowledge in the learning process. Such ex-plainability is essential both for practical application of inductive technology, and for integrating the results of learning back into an existing knowledge-base. We apply this method to two process control problems, a water tank network and an ore grinding process used in the mining industry. Surprisingly, in addition to achieving explainability the classificational accuracy of the induced rules is also increased. We show how the value of the qualitative models can be quantified in terms of their equivalence to additional training examples, and finally discuss possible extensions.

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 "Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ID2-of-3: Constructive Induction of M of-N Concepts for Discriminators in Decision Trees")
  Member "A Divide-and-Conquer Approach to Learning from Prior Knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Automated Decomposition of Model-based Learning Problems")

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