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: "Simplifying Decision Trees: A Survey"
  Abstract: Induced decision trees are an extensively-researched solution to classification tasks. For many practical tasks, the trees produced by tree-generation algorithms are not comprehensible to users due to their size and complexity. Although many tree induction algorithms have been shown to produce simpler, more comprehensible trees (or data structures derived from trees) with good classification accuracy, tree simplification has usually been of secondary concern relative to accuracy and no attempt has been made to survey the literature from the perspective of simplification. We present a framework that organizes the approaches to tree simplification and summarize and critique the approaches within this framework. The purpose of this survey is to provide researchers and practitioners with a concise overview of tree-simplification approaches and insight into their relative capabilities. In our final discussion, we briefly describe some empirical findings and discuss the application of tree induction algorithms to case retrieval in case-based reasoning systems.

Connected through hyperedge HE-1 (induced by source paper "Refining Conversational Case Libraries"):
  with members:
    - "NACODAE: Navy Conversational Decision Aids Environment"
    - "Context-Sensitive Feature Selection for Lazy Learners"
    - "Using Decision Trees to Improve Case-Based Learning"
    - "Learning to Refine Case Libraries:"
    - "Correcting for Length Biasing in Conversational Case Scoring"
    - "A Model-Based Approach for Supporting Dialogue Inferencing in a Conversational Case-Based Reasoner"
    - "Supporting Conversational Case-Based Reasoning in an Integrated Reasoning Framework  Conversational Case-Based Reasoning"

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"
    - "Case-Based Learning: Beyond Classification of Feature Vectors"

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: Theory