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: "Evaluation and Ordering of Rules Extracted from Feedforward Networks"
  Abstract: Rules extracted from trained feedforward networks can be used for explanation, validation, and cross-referencing of network output decisions. This paper introduces a rule evaluation and ordering mechanism that orders rules extracted from feedforward networks based on three performance measures. Detailed experiments using three rule extraction techniques as applied to the Wisconsin breast cancer database, illustrate the power of the proposed methods. Moreover, a method of integrating the output decisions of both the extracted rule-based system and the corresponding trained network is proposed. The integrated system provides further improvements.

Connected through hyperedge HE-1 (induced by source paper "Draft Symbolic Representation of Neural Networks"):
  with members:
    - "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping"
    - "Noisy Time Series Prediction using Symbolic Representation and Recurrent Neural Network Grammatical Inference"

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: Neural_Networks