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 "Heterogeneous Uncertainty Sampling for Supervised Learning"):
  Abstract: Uncertainty sampling methods iteratively request class labels for training instances whose classes are uncertain despite the previous labeled instances. These methods can greatly reduce the number of instances that an expert need label. One problem with this approach is that the classifier best suited for an application may be too expensive to train or use during the selection of instances. We test the use of one classifier (a highly efficient probabilistic one) to select examples for training another (the C4.5 rule induction program). Despite being chosen by this heterogeneous approach, the uncertainty samples yielded classifiers with lower error rates than random samples ten times larger.

Includes members:
  Member "More Efficient Windowing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Incremental Reduced Error Pruning")
  Member "Information-based objective functions for active data selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A Practical Bayesian Framework for Backprop Networks")
  Member "Learning Trees and Rules with Set-valued Features":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Stochastic Propositionalization of Non-Determinate Background Knowledge")
  Member "Context-sensitive learning methods for text categorization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Using and combining predictors that specialize")
  Member "Query by Committee":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Active Learning with Committees for Text Categorization")

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: Theory