Movie Success Prediction Using Naïve Baye, Logistic Regression and Support Vector Machine

Abstract

As a billion-dollar industry, the entertainment sector continues to grow rapidly. This industry
has proven to be very profitable if done correctly, with new milestones being reached almost
every day. Because movies require such large outlays of both time and money, it only makes
sense to attempt to foresee the outcome in advance. This problem has been addressed by
developing a model that can forecast whether or not a film will be considered a success.
There are three machine learning algorithms being compared here: Naive Bayes, Logistic
Regression, and Support Vector Machine (SVM) on the MOVIE dataset.
SVM, Naive Bayes, and Logistic Regression are all terms that can be used to describe this
model.