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: "The Potential of Prototype Styles of Generalization"
  Abstract: There are many ways for a learning system to generalize from training set data. This paper presents several generalization styles using prototypes in an attempt to provide accurate generalization on training set data for a wide variety of applications. These generalization styles are efficient in terms of time and space, and lend themselves well to massively parallel architectures. Empirical results of generalizing on several real-world applications are given, and these results indicate that the prototype styles of generalization presented have potential to provide accurate generalization for many applications.

Connected through hyperedge HE-1 (induced by source paper "Priority ASOCS  ASOCS models have two significant advantages over other learning models:"):
  with members:
    - "Automatic Feature Extraction in Machine Learning"
    - "Towards a General Distributed Platform for Learning and Generalization and Word Perfect Corp. 1 Introduction"
    - "A VLSI Implementation of a Parallel, Self-Organizing Learning Model"
    - "A Multi-Chip Module Implementation of a Neural Network"

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