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America's Next Top (Statistical) Model
Goal of the Competition
US presidential elections come but once every 4 years, and this one's a big one. The new president will help shape policies on education, healthcare, energy, the environment, international relations, aid, and more. There are lots of people trying to predict what will happen. Can you top them?
In this challenge, you'll predict the percent of each state that will vote for each candidate. You can use any data you can get your hands on. Come election night, we'll see who's model had the best vision for the country!
What's in this Repository
This repository contains code volunteered from leading competitors in the America's Next Top (Statistical) Model on DrivenData. Included code is open source under the MIT License.
Winning code for other DrivenData competitions is available in the competition-winners repository.
Winning Submissions
| Place | Team or User | Score | Summary of Model |
|---|---|---|---|
| 1 | tallmeasure | 0.0244 | I used these polls to make 3 predictions. The first is just an average prediction based on the state polls. The second is a prediction based on demographics. I used regression analyses to predict state results based on demographic variables. And the third prediction is based on polls of comparable states. |
| 2 | Noriega-Santoyo | 0.0280 | Categories were assigned to each state using critical and extensive domain knowledge, and modeling expertise. After the scenarios were assigned to each state, a modeling method was applied to produce the prediction (weighted average, average trend, etc.). |