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 "A proposal for variable selection in the Cox model"):
  Abstract: We propose a new method for variable selection and estimation in Cox's proportional hazards model. Our proposal minimizes the log partial likelihood subject to the sum of the absolute values of the parameters being bounded by a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactly zero and hence gives interpretable models. The method is a variation of the "lasso" proposal of Tibshirani (1994), designed for the linear regression context. Simulations indicate that the lasso can be more accurate than stepwise selection in this setting.

Includes members:
  Member "Regression shrinkage and selection via the lasso":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Penalisation multiple adaptative un nouvel algorithme de regression, la penalisation multiple adapta-tive. Cet algorithme represente")

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: Probabilistic_Methods