Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens
Abstract
Classification trees, usually used as a nonlinear, nonparametric classification method, can also provide a powerful framework for comparing, assessing, and combining information from different expert systems, by treating their predictions as the independent variables in a classification tree analysis. This paper discusses the applied problem of classifying chemicals as human carcinogens. It shows how classification trees can be used to compare the information provided by ten different carcinogen classification expert systems, construct an improved "hybrid" classification system from them, and identify cost-effective combinations of assays (the inputs to the expert systems) to use in classifying chemicals in future.
Cite
Text
Cox. "Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens." Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999.Markdown
[Cox. "Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens." Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999.](https://mlanthology.org/aistats/1999/cox1999aistats-causal/)BibTeX
@inproceedings{cox1999aistats-causal,
title = {{Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens}},
author = {Cox, Louis Anthony},
booktitle = {Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics},
year = {1999},
pages = {18-26},
volume = {R2},
url = {https://mlanthology.org/aistats/1999/cox1999aistats-causal/}
}