predicting income based on limited features
This project was completed in collaboration with Alanna Besaw, Patrick Cavins, Anna Haas, and William Holder
This was a 6-hour team hackathon project, and we were tasked to create an accurate model to predict the probability that people earned over $50,000. We were given the limitation that we could only use 20 features to create our model (and we were not able to use principle component analysis to narrow down the number of features used to build the model).
The project can be found here.
The blog post about this project can be found here.
Photo by Sharon McCutcheon on Unsplash