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: "Knowledge Discovery in International Conflict Databases"
  Abstract: Artificial Intelligence is heavily supported by military institutions, while practically no effort goes into the investigation of possible contributions of AI to the avoidance and termination of crises and wars. This paper makes a first step into this direction by investigating the use of machine learning techniques for discovering knowledge in international conflict and conflict management databases. We have applied similarity-based case retrieval to the KOSIMO database of international conflicts. Furthermore, we present results of analyzing the CONFMAN database of successful and unsuccessful conflict management attempts with an inductive decision tree learning algorithm. The latter approach seems to be particularly promising, as conflict management events apparently are more repetitive and thus better suited for machine-aided analysis.

Connected through hyperedge HE-1 (induced by source paper "The Possible Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods"):
  with members:
    - "A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features"

Connected through hyperedge HE-2 (induced by source paper "Irrelevant Features and the Subset Selection Problem"):
  with members:
    - "Theory Revision in Fault Hierarchies"
    - "An Optimized Theory Revision Module"
    - "Expectation-Based Selective Attention for Visual Monitoring and Control of a Robot Vehicle"
    - "Feature Subset Selection as Search with Probabilistic Estimates"
    - "NP-Completeness of Searches for Smallest Possible Feature Sets a subset of the set of all"
    - "Cost-sensitive feature reduction applied to a hybrid genetic algorithm"
    - "Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms"
    - "Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome"

Connected through hyperedge HE-3 (induced by source paper "Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome"):
  with members:
    - "Irrelevant Features and the Subset Selection Problem"
    - "Structural Regression Trees"
    - "Automatic Parameter Selection by Minimizing Estimated Error"
    - "Beyond Correlation: Bringing Artificial Intelligence to Events Data"

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