DocumentCode
3756664
Title
Health Outcome Prediction with Multiple Models and Dempster-Shafer Theory
Author
Michael Bauer
Author_Institution
Dept. of Comput. Sci., Univ. of Western Ontario, London, ON, Canada
fYear
2015
Firstpage
781
Lastpage
786
Abstract
Can multiple predictive models be combined to predict health care outcomes? In this paper, we explore this question by considering the use of multiple predictive models as "evidence" and formulate a multi-model approach to prediction based on Dempster-Shafer´s Theory of Evidence. Given the accuracy measures of multiple models, we propose a formulation of a combined predictive model based on Dempster-Shafer´s Theory. We then evaluate this approach on a set of data and compare it to predictions by the individual models.
Keywords
"Predictive models","Data models","Mathematical model","Uncertainty","Computational modeling","Bayes methods","Sensors"
Publisher
ieee
Conference_Titel
Computational Science and Computational Intelligence (CSCI), 2015 International Conference on
Type
conf
DOI
10.1109/CSCI.2015.80
Filename
7424195
Link To Document