human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "An Improved Algorithm for Incremental Induction of Decision Trees"):
  Abstract: Technical Report 94-07 February 7, 1994 (updated April 25, 1994) This paper will appear in Proceedings of the Eleventh International Conference on Machine Learning. Abstract This paper presents an algorithm for incremental induction of decision trees that is able to handle both numeric and symbolic variables. In order to handle numeric variables, a new tree revision operator called `slewing' is introduced. Finally, a non-incremental method is given for finding a decision tree based on a direct metric of a candidate tree.

Includes members:
  Member "Machine Learning Learning to Predict by the Methods of Temporal Differences Keywords: Incremental learning, prediction,":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "TDLeaf(): Combining Temporal Difference learning with game-tree search.")
  Member "Theory Revision in Fault Hierarchies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "An Optimized Theory Revision Module")
  Member "Integration of Case-Based Reasoning and Neural Networks Approaches for Classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "(1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Case-Based Reasoning: Foundational Issues, Methodological")
  Member "Lazy Induction Triggered by CBR":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "A System for Induction of Oblique Decision Trees")
  Member "Induction of Oblique Decision Trees":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine")
  Member "Learning Classification Trees":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine")
  Member "Relating Relational Learning Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "LEARNING CONCEPTS BY ASKING QUESTIONS")
  Member "Geometric Comparison of Classifications and Rule Sets*":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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