human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Case-Based Learning: Beyond Classification of Feature Vectors"
  Abstract: The dominant theme of case-based research at recent ML conferences has been on classifying cases represented by feature vectors. However, other useful tasks can be targeted, and other representations are often preferable. We review the recent literature on case-based learning, focusing on alternative performance tasks and more expressive case representations. We also highlight topics in need of additional research.

Connected through hyperedge HE-1 (induced by source paper "A Case Study of Case-Based CBR"):
  with members:
    - "Acquiring Case Adaptation Knowledge: A Hybrid Approach"
    - "Supporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning"
    - "Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning"
    - "Case-Based Similarity Assessment: Estimating Adaptability from Experience"

Connected through hyperedge HE-2 (induced by source paper "NACODAE: Navy Conversational Decision Aids Environment"):
  with members:
    - "(1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Case-Based Reasoning: Foundational Issues, Methodological"
    - "Refining Conversational Case Libraries"
    - "Simplifying Decision Trees: A Survey"

Question: Please tell me which class the center node 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