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: "Machine Learning by Function Decomposition"
  Abstract: We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and their definitions. This effectively decomposes the problem into smaller, less complex problems. The method is inspired by the Boolean function decomposition approach to the design of digital circuits. To cope with high time complexity of finding an optimal decomposition, we propose a suboptimal heuristic algorithm. The method, implemented in program HINT (HIerarchy Induction Tool), is experimentally evaluated using a set of artificial and real-world learning problems. It is shown that the method performs well both in terms of classification accuracy and discovery of meaningful concept hierarchies.

Connected through hyperedge HE-1 (induced by source paper "Constructing Intermediate Concepts by Decomposition of Real Functions"):
  with members:
    - "A dataset decomposition approach to data mining and machine discovery"

Connected through hyperedge HE-2 (induced by source paper "Pattern Theoretic Feature Extraction and Constructive Induction"):
  with members:
    - "A dataset decomposition approach to data mining and machine discovery"
    - "APPLICATION OF ESOP MINIMIZATION IN MACHINE LEARNING AND KNOWLEDGE DISCOVERY"

Connected through hyperedge HE-3 (induced by source paper "A dataset decomposition approach to data mining and machine discovery"):
  with members:
    - "Constructing Intermediate Concepts by Decomposition of Real Functions"
    - "Pattern Theoretic Feature Extraction and Constructive Induction"

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: Theory