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 :
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