human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Using Neural Networks for Descriptive Statistical Analysis of Educational Data"):
  Abstract: In this paper we discuss the methodological issues of using a class of neural networks called Mixture Density Networks (MDN) for discriminant analysis. MDN models have the advantage of having a rigorous probabilistic interpretation, and they have proven to be a viable alternative as a classification procedure in discrete domains. We will address both the classification and interpretive aspects of discriminant analysis, and compare the approach to the traditional method of linear discrimin- ants as implemented in standard statistical packages. We show that the MDN approach adopted performs well in both aspects. Many of the observations made are not restricted to the particular case at hand, and are applicable to most applications of discriminant analysis in educational research. fl URL: http://www.cs.Helsinki.FI/research/cosco/

Includes members:
  Member "Hierarchical Mixtures of Experts and the EM Algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Forecasting electricity demand using nonlinear mixture of experts")
  Member "A Practical Bayesian Framework for Backprop Networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Information-based objective functions for active data selection")
  Member "Probabilistic Instance-Based Learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Comparing Predictive Inference Methods for Discrete Domains")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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