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: "The evaluation of Anapron: A case study in evaluating a case-based system"
  Abstract: This paper presents a case study in evaluating a case-based system. It describes the evaluation of Anapron, a system that pronounces names by a combination of rule-based and case-based reasoning. Three sets of experiments were run on Anapron: a set of exploratory measurements to profile the system's operation; a comparison between Anapron and other name-pronunciation systems; and a set of studies that modified various parts of the system to isolate the contribution of each. Lessons learned from these experiments for CBR evaluation methodology and for CBR theory are discussed. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories of Cambridge, Massachusetts; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories. All rights reserved.

Connected through hyperedge HE-1 (induced by source paper "A comparison of Anapron with seven other name-pronunciation systems"):
  with members:
    - "Improving accuracy by combining rule-based and case-based reasoning"
    - "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping"

Connected through hyperedge HE-2 (induced by source paper "Improving accuracy by combining rule-based and case-based reasoning"):
  with members:
    - "Theory Refinement Combining Analytical and Empirical Methods"
    - "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping"
    - "Language-Independent Data-Oriented Grapheme-to-Phoneme Conversion"
    - "Case-based Acquisition of User Preferences for Solution Improvement in Ill-Structured Domains"
    - "A comparison of Anapron with seven other name-pronunciation systems"

Connected through hyperedge HE-3 (induced by source paper "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping"):
  with members:
    - "Experiments on the Transfer of Knowledge between Neural Networks Reprinted from: Computational Learning Theory and"
    - "Statistical Tests for Comparing Supervised Classification Learning Algorithms"
    - "Constructing Nominal Xof-N Attributes"
    - "Improving accuracy by combining rule-based and case-based reasoning"
    - "Framework for Combining Symbolic and Neural Learning rule extraction from neural networks the KBANN algorithm"
    - "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine"
    - "Draft Symbolic Representation of Neural Networks"
    - "Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models"

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