Shapley values from a Gaussian process regression rank income, workforce, HIV testing, unemployment, and population as the most influential socio-economic predictors of tuberculosis infection rates, but the regression only matches 10 of 87 Russian regions within 10 percent error.
Agent-based mathematical model of covid-19 spread in novosibirsk region: Identifiability, optimization and forecasting
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.soc-ph 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Feature importance of socio-economic parameters in Tuberculosis modeling
Shapley values from a Gaussian process regression rank income, workforce, HIV testing, unemployment, and population as the most influential socio-economic predictors of tuberculosis infection rates, but the regression only matches 10 of 87 Russian regions within 10 percent error.