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: "Draft Symbolic Representation of Neural Networks"
  Abstract: An early and shorter version of this paper has been accepted for presenta tion at IJCAI'95.

Connected through hyperedge HE-1 (induced by source paper "A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping"):
  with members:
    - "Experiments on the Transfer of Knowledge between Neural Networks Reprinted from: Computational Learning Theory and"
    - "Statistical Tests for Comparing Supervised Classification Learning Algorithms"
    - "Constructing Nominal Xof-N Attributes"
    - "Improving accuracy by combining rule-based and case-based reasoning"
    - "Framework for Combining Symbolic and Neural Learning rule extraction from neural networks the KBANN algorithm"
    - "Mingers, 1989 J. Mingers. An empirical comparison of pruning methods for decision tree induction. Machine"
    - "Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models"
    - "Generalizing from Case Studies: A Case Study"

Connected through hyperedge HE-2 (induced by source paper "Noisy Time Series Prediction using Symbolic Representation and Recurrent Neural Network Grammatical Inference"):
  with members:
    - "PREDICTING SUNSPOTS AND EXCHANGE RATES WITH CONNECTIONIST NETWORKS"
    - "Extraction of Rules from Discrete-Time Recurrent Neural Networks"
    - "POWER OF NEURAL NETS"
    - "Statistical Mechanics of Nonlinear Nonequilibrium Financial Markets: Applications to Optimized Trading"

Connected through hyperedge HE-3 (induced by source paper "Evaluation and Ordering of Rules Extracted from Feedforward Networks"):
  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: Neural_Networks