human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "symbolic regression by random search"
  Abstract: Purpose: To compare symbolic regression by genetic programming (SRGP) with symbolic regression by random search (SRRS), a novel method for symbolic regression described herein. Methods: We limit our problem space to N binary trees, m terminals and n functions, then use a dense enumeration of full binary trees to perform uniform random sampling from the set of all permitted equations. We compare a single basic configuration of symbolic regression by genetic programming with symbolic regression by random search using 1000 randomly generated problems. We perform a hyperparameter search with 50 randomly generated symbolic regression problems and 198 randomly generated hyperparameter configurations, examining the performance of SRGP against SRRS. Results: For the single configuration experiment, SRGP outperformed SRRS in 49.0% of problems, random search was best in 26.2% of problems, and there was a tie in 24.8% of problems. Of the cases that were not tied, genetic programming was best in 65.6% of experiments (99% CI, [60.7%, 69.2%]). Of the cases that were not tied in the hyperparameter search, SRGP was best in 44% (99% CI, [41%, 48%]) of cases. The average random configuration of SRGP performs worse than does SRRS.

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NE(Neural and Evolutionary Computing)