naivebayes for email spam detection

Spam detection model using naive bayes. Applies count vectorizer on the data then trains the model on the spamorham.csv dataset.

Usage

main.py prepares the data, trains the model, outputs the fitnes, and saves the model to a pickle file. Running main.py will retrain the model and save a new pickle file.

The accuracy of the model rarely fall below 0.97% for English inputs under 1000 characters.