International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 44 |
Year of Publication: 2021 |
Authors: D.M.L. Dissanayake, V.G.T.N. Vidanagama |
10.5120/ijca2021921847 |
D.M.L. Dissanayake, V.G.T.N. Vidanagama . Early Prediction of Movie Success using Machine Learning Models. International Journal of Computer Applications. 183, 44 ( Dec 2021), 14-21. DOI=10.5120/ijca2021921847
The film industry is a multi-billion-dollar business that is spread all over the world. A very high number of films are being released every year. But only a few are successful and most are failures. If the success of a movie can be predicted and reduce the uncertainty at the early stages of the movie-making process, that will make a significant impact on the film industry because of the immense investments that are made. The success of a movie is based on several factors related to the past, present and future. By identifying the factors that are relevant to the success of a movie, it can be predicted accurately. Creating predictive models with the use of machine learning has become a trend in the recent past due to the availability of large volumes of data and high computational capabilities. Prediction models and currently available machine learning methods can be used to predict the success of a movie. This paper describes a novel approach using machine learning methods to predict the success of a movie in advance. In this paper, multiple regression and classification methods were used for training and testing the dataset and their performances were evaluated to identify the well-fitted model. The Support Vector Machine model showed a movie success prediction rate of 100% on the test data.