Impeachment Prediction

Oct 26, 2023 · 1 min read

This project objective was to use Machine Learning models to predict which legislative representative of Brazil would vote in favor or oppose to the impeachment of Brazilian ex-president Dilma Rousseff

The model was built using a Decision Forest model, and their inputs was the votes of multiple legislative acts of Brazilian legislative representative and some public news of representatives that reveleated their vote.

The model correctly predicted the outcome and also achieved a great accuracy in obtaining the number of total votes in favor and opposition.

To see more details, check the post: Data Science for predicting impeachment votes

Politics Machine Learning Forecasting
Gustavo De Mari Pereira
Authors
Gustavo De Mari Pereira (he/him)
Data Scientist & Machine Learning Engineer
M.S. in Computer Science from IME-USP, focused on Reinforcement Learning. Founder of 2 companies, 10+ years of experience working with large-scale databases and building end-to-end ML pipelines. Kaggle competitor and Scikit-learn contributor.