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

The entertainment industry is a rapidly growing billion-dollar industry. With new milestones being reached almost every day, this industry has proved itself to be a very profitable business, if done correctly. Since huge investments are involved in the production and making of movies, both in terms of time and money, it would only make sense to try to predict the outcome beforehand. In an attempt to tackle this problem, we have built a model that predicts whether or not a movie can be called a success. The model compares the performance of three machine learning algorithms i.e. Naive Bayes, Logistic Regression, and Support Vector Machine (SVM), over two different datasets, to observe which performs better. We have illustrated the model, as well as its results, findings, and observations in this literature.