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Estimating neighbourhood death rates using the random forest algorithm
Andrew John George Cairns
*
, Jie Wen
, Torsten Kleinow
*
Corresponding author for this work
School of Mathematical & Computer Sciences
Research output
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Article
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INIS
randomness
100%
algorithms
100%
mortality
100%
forests
100%
death
100%
economics
83%
populations
33%
data
16%
levels
16%
information
16%
exercise
16%
nonlinear problems
16%
range
16%
capture
16%
education
16%
availability
16%
increasing
16%
metrics
16%
indicators
16%
income
16%
diet
16%
crime
16%
air pollution
16%
Social Sciences
Random Forest
100%
Air Pollution
50%
Socio-Economic Indicators
50%
Crime Rate
50%
Data Science
50%
Education
50%
Economic Information
50%
English
50%
Prevalence
50%
Mathematics
Nonlinear
100%
Death Rate
100%
Healthcare
100%
Earth and Planetary Sciences
Air Pollution
100%
English
100%
Economics, Econometrics and Finance
Economic Indicator
100%
Economics of Information
100%
Psychology
Healthcare
100%