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: "Rule Induction and Instance-Based Learning: A Unified Approach"
  Abstract: This paper presents a new approach to inductive learning that combines aspects of instance-based learning and rule induction in a single simple algorithm. The RISE system searches for rules in a specific-to-general fashion, starting with one rule per training example, and avoids some of the difficulties of separate-and-conquer approaches by evaluating each proposed induction step globally, i.e., through an efficient procedure that is equivalent to checking the accuracy of the rule set as a whole on every training example. Classification is performed using a best-match strategy, and reduces to nearest-neighbor if all generalizations of instances were rejected. An extensive empirical study shows that RISE consistently achieves higher accuracies than state-of-the-art representatives of its "parent" paradigms (PEBLS and CN2), and also outperforms a decision-tree learner (C4.5) in 13 out of 15 test domains (in

Connected through hyperedge HE-1 (induced by source paper "Inductive CBR for Customer Support"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Distance Induction in First Order Logic used for classification via a k-nearest-neighbor process. Experiments on"):
  with members:
    - "(1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Case-Based Reasoning: Foundational Issues, Methodological"

Connected through hyperedge HE-3 (induced by source paper "Rule Generation and Compaction in the wwtp"):
  with members:
    - "LINNEO A Classification Methodology for Ill-structured Domains"

Connected through hyperedge HE-4 (induced by source paper "Using Partitioning to Speed Up Specific-to-General Rule Induction"):
  with members:
    - "Concept Learning and the Problem of Small"

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