Predicting Popular Government, an analys is of states

By Justin Hines

This is a final project for Data Driven Modeling taught by Jake Hofman.

This project aims to predict the popularity of governemntal articles using a multi-class bernoulli naive bayes classifier.

Run make to download the dataset, filter, and apply the classifier. Results will be stored in log/.  All tsv data sets will be in tsv organized by dstate.  Final filtered tsvs will be in tsv/{STATE}/tsvs/

Run make bayes to run the bayes classifier on a dataset, or python bayes.py in the src/ directory.

The final report is included in docs/