• Computer Science
  • Published 2002

Toward a High-performance System for Symbolic and Statistical Modeling

@inproceedings{Zhou2002TowardAH,
  title={Toward a High-performance System for Symbolic and Statistical Modeling},
  author={Neng-Fa Zhou and Taisuke Sato},
  year={2002}
}
We present in this paper a state-of-the-art implementation of PRISM, a language based on Prolog that supports statistical modeling and learning. We start with an interpreter of the language that incorporates a naive learning algorithm, and then turn to improve the interpreter. One of the improvements is to refine the learning algorithm such that it works on explanation graphs rather than flat explanations. Tabling is used to construct explanation graphs so that variant subgoals do not need to… CONTINUE READING

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