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: "Context-Sensitive Feature Selection for Lazy Learners"

Connected through hyperedge HE-1 (induced by source paper "ICML-96 Workshop "Learning in context-sensitive domains" Bari, Italy. Dynamically Adjusting Concepts to Accommodate Changing Contexts"):
  with members:
    - "Efficient Feature Selection in Conceptual Clustering"

Connected through hyperedge HE-2 (induced by source paper "Refining Conversational Case Libraries"):
  with members:
    - "NACODAE: Navy Conversational Decision Aids Environment"
    - "Using Decision Trees to Improve Case-Based Learning"
    - "Learning to Refine Case Libraries:"
    - "Simplifying Decision Trees: A Survey"
    - "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-3 (induced by source paper "Learning to Refine Case Libraries:"):
  with members:
    - "Using Decision Trees to Improve Case-Based Learning"
    - "Refining Conversational Case Libraries"

Connected through hyperedge HE-4 (induced by source paper "Context-sensitive attribute estimation in regression"):
  with members:
    - "Employing Linear Regression in Regression Tree Leaves"
    - "Estimating Attributes: Analysis and Extensions of RELIEF"
    - "Prognosing the Survival Time of the Patients with the Anaplastic Thyroid Carcinoma with Machine Learning"
    - "Overcoming the myopia of inductive learning algorithms with RELIEFF"
    - "Recognition and Exploitation of Contextual Clues via Incremental Meta-Learning (Extended Version)"

Connected through hyperedge HE-5 (induced by source paper "The Management of Context-Sensitive Features: A Review of Strategies"):
  with members:
    - "Recognition and Exploitation of Contextual Clues via Incremental Meta-Learning (Extended Version)"
    - "A Patient-Adaptive Neural Network ECG Patient Monitoring Algorithm"
    - "Concept Learning and Flexible Weighting"

Connected through hyperedge HE-6 (induced by source paper "An adaptation of Relief for attribute estimation in regression"):
  with members:
    - "Flexible Metric Nearest Neighbor Classiflcation"
    - "Employing Linear Regression in Regression Tree Leaves"
    - "Estimating Attributes: Analysis and Extensions of RELIEF"
    - "Overcoming the myopia of inductive learning algorithms with RELIEFF"

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