The map above allows you to construct hypothetical scenarios based on 10 tunable parameters that are applied equally to all US counties. For example, if you want to answer the question “how could the election have been different if the percentage of people with at least a bachelor’s degree had been 2% higher nationwide?” you can simply toggle that parameter up to 1.02 and click “Submit” to find out.
The predictions are driven by a random forest classification model that has been tuned and trained on 71 distinct county-level attributes. The model has a predictive accuracy of 94.6% and an ROC AUC score of 96%. When you adjust the tunable parameters and hit “Submit,” the model takes in the new data and updates the predicted outcome.