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 "Selection of Relevant Features and Examples in Machine Learning"):
  Abstract: In this survey, we review work in machine learning on methods for handling data sets containing large amounts of irrelevant information. We focus on two key issues: the problem of selecting relevant features, and the problem of selecting relevant examples. We describe the advances that have been made on these topics in both empirical and theoretical work in machine learning, and we present a general framework that we use to compare different methods. We close with some challenges for future work in this area.

Includes members:
  Member "A Method of Combining Multiple Probabilistic Classifiers through Soft Competition on Different Feature Sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Combining estimates in regression and classification")
  Member "Flexible Metric Nearest Neighbor Classiflcation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Cross-Validation and the Bootstrap: Estimating the Error Rate of a Prediction Rule")
  Member "Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Issues in the Integration of Data Mining and Data Visualization Visualizing the Simple Bayesian Classifier")

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