Project: The Spam Detection Program

This project is a very rudimentary program that uses binary dictionaries and uses the Bayes theorem to determine the probability of an email being either spam or "ham" (not spam).

The Naïve Bayes Spam Filter equation takes the probability of a spam occurring (P(A)), the probability of spam not occurring (P(B)), the conditional probability of a spam email occurring, given that a specific email is not spam also occurs (P(A/B)), and the conditional probability of event spam not occurring, given that a specific email is spam also occurs (P(B/A)). This forms into the equation: P(A|B) = P(B|A) * P(A) / P(B)

The conditional probability (P(A/B)) is what then determines if the email is considered to be spam or not spam.

If you wish to take a look at the code behind this project, click the photo to be taken to my GitHub where you can find all of my projects.