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: "Individual and Collective Prognostic Prediction"
  Abstract: The prediction of survival time or recurrence time is an important learning problem in medical domains. The Recurrence Surface Approximation (RSA) method is a natural, effective method for predicting recurrence times using censored input data. This paper introduces the Survival Curve RSA (SC-RSA), an extension to the RSA approach which produces accurate predicted rates of recurrence, while maintaining accuracy on individual predicted recurrence times. The method is applied to the problem of breast cancer recurrence using two different datasets.

Connected through hyperedge HE-1 (induced by source paper "A Neural Network Model for Prognostic Prediction"):
  with members:
    - "An Inductive Learning Approach to Prognostic Prediction"

Connected through hyperedge HE-2 (induced by source paper "An Inductive Learning Approach to Prognostic Prediction"):
  with members:
    - "Irrelevant Features and the Subset Selection Problem"
    - "A Neural Network Model for Prognostic Prediction"

Connected through hyperedge HE-3 (induced by source paper "Feature Selection via Mathematical Programming"):
  with members:
    - "Book Review  Introduction to the Theory of Neural Computation Reviewed by: 2"
    - "Irrelevant Features and the Subset Selection Problem"
    - "Bilinear Separation of Two Sets in n-Space"
    - "Mathematical Programming in Neural Networks"
    - "Parsimonious Least Norm Approximation"

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