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: "Data Mining for Association Rules with Unsupervised Neural Networks"
  Abstract: results for Gaussian mixture models and factor analysis are discussed.

Connected through hyperedge HE-1 (induced by source paper "The EM Algorithm for Mixtures of Factor Analyzers"):
  with members:
    - "Data Mining for Association Rules with Unsupervised Neural Networks"
    - "A HIERARCHICAL COMMUNITY OF EXPERTS"
    - "EM Algorithms for PCA and SPCA"
    - "Recognizing Handwritten Digits Using Mixtures of Linear Models"

Connected through hyperedge HE-2 (induced by source paper "Recognizing Handwritten Digits Using Mixtures of Linear Models"):
  with members:
    - "Data Mining for Association Rules with Unsupervised Neural Networks"
    - "Factor Analysis Using Delta-Rule Wake-Sleep Learning"
    - "Comparison of Neural and Statistical Classifiers| Theory and Practice"
    - "Mixtures of Probabilistic Principal Component Analysers"
    - "In  Fast Non-Linear Dimension Reduction"
    - "The EM Algorithm for Mixtures of Factor Analyzers"
    - "Constraint Tangent Distance for On-line Character Recognition"

Connected through hyperedge HE-3 (induced by source paper "Generative Models for Discovering Sparse Distributed Representations"):
  with members:
    - "References "Using Neural Networks to Identify Jets", Kohonen, "Self Organized Formation of Topologically Correct Feature"
    - "Unsupervised Learning by Convex and Conic Coding"
    - "Pattern analysis and synthesis in attractor neural networks"
    - "The Rectified Gaussian Distribution"
    - "Data Mining for Association Rules with Unsupervised Neural Networks"
    - "A HIERARCHICAL COMMUNITY OF EXPERTS"
    - "Continuous sigmoidal belief networks trained using slice sampling"
    - "Factor Analysis Using Delta-Rule Wake-Sleep Learning"

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