Modeling Voters Turnout
How to use prediction to forecast future values like tomorrow's air quality in the city of Paris? How to make prediction or estimation of the average voter turnout in a particular county or region?
How to use prediction to forecast future values like tomorrow's air quality in the city of Paris? How to make prediction or estimation of the average voter turnout in a particular county or region?
Prediction is an important part of spatial data science. This supervised machine learning algorithm allows to use existing data to train models that may be useful for predictive analysis.
In this exercise, the Forest-based Classification and Regression help to predict voter turnout in USA by testing several variables (Median Age of the 2019, Income Per Capita in 2019, Education: whether High School or No Diploma, Distance variables, Categorical variables, Variable of election competitiveness and so on).
These models can provide insights into how different factors may influence voter turnout and help anticipate the level of participation in future elections thereby providing valuable information for election planning, resource allocation, and political analysis.
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