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 "Average-Case Analysis of a Nearest Neighbor Algorithm"):
  Abstract: In this paper we present an average-case analysis of the nearest neighbor algorithm, a simple induction method that has been studied by many researchers. Our analysis assumes a conjunctive target concept, noise-free Boolean attributes, and a uniform distribution over the instance space. We calculate the probability that the algorithm will encounter a test instance that is distance d from the prototype of the concept, along with the probability that the nearest stored training case is distance e from this test instance. From this we compute the probability of correct classification as a function of the number of observed training cases, the number of relevant attributes, and the number of irrelevant attributes. We also explore the behavioral implications of the analysis by presenting predicted learning curves for artificial domains, and give experimental results on these domains as a check on our reasoning.

Includes members:
  Member "Oblivious Decision Trees and Abstract Cases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms")
  Member "Towards a Better Understanding of Memory-Based Reasoning Systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Logarithmic-Time Updates and Queries in Probabilistic Networks")
  Member "Induction of One-Level Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine")
  Member "An Analysis of Bayesian Classifiers (1988), involves the formulation of average-case models for specific algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Towards a Better Understanding of Memory-Based Reasoning Systems")
  Member "Inductive Bias in Case-Based Reasoning Systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features")
  Member "PAC Analyses of a `Similarity Learning' IBL Algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Towards a Theory of Optimal Similarity Measures way of learning a similarity measure from the")

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: Case_Based