A Study of Predict Sales Based on Random Forest Classification

The sales of movie industry have increased by 4.2% in 2015 compared to 2014 as reported by Korean Film Industry Council. This result can be attributed to the increase in the ticket price in addition to the expansion of the online market. Although South Korean’s average annual movie consumption per capita is among the highest in the world, it is still difficult to estimate the probability of success for any given movie, and as such speculations come with high risks. Even among Holly Wood movies, only 2 or 3 out of 10 movies are successful, and there are many difficulties from development to release. Domestic movie industry also faces high risk, and the average profit from film investment in 2015 was at -7.2%, which shows the extreme difficulty of generating profit from investing in the movie industry. The attempts to minimize the risks by estimating the movie’s success, such as attempting to estimate the number of audience based on quantitative data and deduction of variables, have been partially successful. However, due to the unforeseen effects of social phenomena, many of these predictions have also resulted in failures, which often inflicts in severe financial losses to the producers. This paper demonstrates the use of statistical approach to predict a movie’s success, by analyzing the correlation between the total sales (dependent variable) and a number of potential influential factors (independent variables). In addition, the significance of each potential factor was quantified using Random Forest algorithm