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: "On Functional Relation between Recognition Error and Class-Selective Reject"
  Abstract: This report reviews various optimum decision rules for pattern recognition, namely, Bayes rule, Chow's rule (optimum error-reject tradeoff), and a recently proposed class-selective rejection rule. The latter provides an optimum tradeoff between the error rate and the average number of (selected) classes. A new general relation between the error rate and the average number of classes is presented. The error rate can directly be computed from the class-selective reject function, which in turn can be estimated from unlabelled patterns, by simply counting the rejects. Theoretical as well as practical implications are discussed and some future research directions are proposed.

Connected through hyperedge HE-1 (induced by source paper "An Optimum Decision Rule for Pattern Recognition"):
  with members:
    (none)

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: Probabilistic_Methods