human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition"):
  Abstract: Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering but easy with another. Machine learning is the process of fitting a computer model to a complex function based on properties learned from measured data. In this paper we use machine learning (specifically a support vector machine) to select between heuristics for choosing a variable ordering, outperforming each of the separate heuristics.

Includes members:
  Member "an implementation of cad in maple utilising problem formulation equational constraints and truth table invariance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "truth table invariant cylindrical algebraic decomposition")
  Member "cylindrical algebraic decompositions for boolean combinations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "optimising problem formulation for cylindrical algebraic decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "a piano movers problem reformulated":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using machine learning to improve cylindrical algebraic decomposition")
  Member "program verification in the presence of complex numbers functions with branch cuts etc":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "computing cylindrical algebraic decomposition via triangular decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cylindrical algebraic decomposition with equational constraints")
  Member "machine learning in automated text categorization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "utilizing neural networks and linguistic metadata for early detection of depression indications in text sequences")

Question: Please tell me which class the source paper 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.SC(Symbolic Computation)