Evaluation of Uncertain Inference Models III: The Role of Tuning
Abstract
This study examined the effects of "tuning" the parameters of the incremental function of MYCIN, the independent function of PROSPECTOR, a probability model that assumes independence, and a simple additive linear equation. me parameters of each of these models were optimized to provide solutions which most nearly approximated those from a full probability model for a large set of simple networks. Surprisingly, MYCIN, PROSPECTOR, and the linear equation performed equivalently; the independence model was clearly more accurate on the networks studied.
Cite
Text
Wise et al. "Evaluation of Uncertain Inference Models III: The Role of Tuning." Conference on Uncertainty in Artificial Intelligence, 1987.Markdown
[Wise et al. "Evaluation of Uncertain Inference Models III: The Role of Tuning." Conference on Uncertainty in Artificial Intelligence, 1987.](https://mlanthology.org/uai/1987/wise1987uai-evaluation/)BibTeX
@inproceedings{wise1987uai-evaluation,
title = {{Evaluation of Uncertain Inference Models III: The Role of Tuning}},
author = {Wise, Ben P. and Perrin, Bruce M. and Vaughan, David S. and Yadrick, Robert M.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1987},
pages = {55-62},
url = {https://mlanthology.org/uai/1987/wise1987uai-evaluation/}
}