Movie rating prediction with machine learning algorithms on IMDB data set

Abstract

Predicting movie success with machine learning algorithms has become a very popular research area. There are many algorithms which can be applied on a data set to make movie success prediction if the data set is prepared and represented properly. In this study, we explained how IMDB movie data was used for movie rating prediction. The data set extracted from IMDB was formatted and prepared for datamining algorithms. These algorithms were executed on WEKA application environment and the performances in movie ratings and confusion matrices were obtained. The seven machine learning algorithms used have performed well on the data set with varying performance ratings of 73.5% to 92.7%. Random Forest algorithm had the best performance of 92.7%. This is the highest score obtained among similar studies.