Loading...
Loading...

Go to the content (press return)

Learning causal networks from data: a survey and a new algorithm for recovering possibilistic causal networks

Author
Sangüesa, R.; Cortes, U.
Type of activity
Journal article
Journal
AI communications: the european journal of artificial intelligence
Date of publication
1997-03
Volume
10
Number
1
First page
31
Last page
61
Abstract
Causal concepts play a crucial role in many reasoning tasks. Organised as a model revealing the causal structure of a domain, they can guide inference through relevant knowledge. This is an especially difficult kind of knowledge to acquire, so some methods for automating the induction of causal models from data have been put forth. Here we review those that have a graph representation. Most work has been done on the problem of recovering belief nets from data but some extensions are appearing th...
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group

Participants