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 "Estimating the Accuracy of Learned Concepts"):
  Abstract: This paper investigates alternative estimators of the accuracy of concepts learned from examples. In particular, the cross-validation and 632 bootstrap estimators are studied, using synthetic training data and the foil learning algorithm. Our experimental results contradict previous papers in statistics, which advocate the 632 bootstrap method as superior to cross-validation. Nevertheless, our results also suggest that conclusions based on cross-validation in previous machine learning papers are unreliable. Specifically, our observations are that (i) the true error of the concept learned by foil from independently drawn sets of examples of the same concept varies widely, (ii) the estimate of true error provided by cross-validation has high variability but is approximately unbiased, and (iii) the 632 bootstrap estimator has lower variability than cross-validation, but is systematically biased.

Includes members:
  Member "A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Cross-Validation and the Bootstrap: Estimating the Error Rate of a Prediction Rule")
  Member "Cross-Validation and the Bootstrap: Estimating the Error Rate of a Prediction Rule":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection")
  Member "On the Induction of Intelligible Ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "On Pruning and Averaging Decision Trees")

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