Goal of this exercise is to use a naive version of Bayes' Theorem to classify IMDB movie reviews as either positive (1) or negative (0).

Data sourced from Kaggle. Positive reviews gave scores greater than or equal to 7, negative reviews gave scores less than or equal to 4, on a scale of 1-10. For cleaned CSVs provided in this repository, there are no reviews included that gave neutral scores of 5-6.

Code to clean and sample down the CSVs can be found in the Preparing_CSVs notebook, which used some code from this notebook by Praveen Kotha.

Samples for the train and test sets, without duplicates and fairly evenly distributed between positive and negative reviews, are provided in the main directory as clean_train_sample and clean_test_sample. There are 5000 samples in both the train and the test sample CSVs.