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 "Oblivious Decision Trees and Abstract Cases"):
  Abstract: In this paper, we address the problem of case-based learning in the presence of irrelevant features. We review previous work on attribute selection and present a new algorithm, Oblivion, that carries out greedy pruning of oblivious decision trees, which effectively store a set of abstract cases in memory. We hypothesize that this approach will efficiently identify relevant features even when they interact, as in parity concepts. We report experimental results on artificial domains that support this hypothesis, and experiments with natural domains that show improvement in some cases but not others. In closing, we discuss the implications of our experiments, consider additional work on irrelevant features, and outline some directions for future research.

Includes members:
  Member "Irrelevant Features and the Subset Selection Problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "NP-Completeness of Searches for Smallest Possible Feature Sets a subset of the set of all")
  Member "Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "On the Greediness of Feature Selection Algorithms")
  Member "Using Decision Trees to Improve Case-Based Learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Refining Conversational Case Libraries")
  Member "Induction of Condensed Determinations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "The Power of Decision Tables")
  Member "Average-Case Analysis of a Nearest Neighbor Algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Towards a Better Understanding of Memory-Based Reasoning Systems")
  Member "Fast NP Chunking Using Memory-Based Learning Techniques":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "RAPID DEVELOPMENT OF NLP MODULES WITH MEMORY-BASED LEARNING")

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