Decision Tree Algorithms for Accurate Prediction of Movie Rating

Abstract

In this paper, we aim to find an accurate algorithm for implementing information mining systems utilizing Weka tool to foresee the achievement or disappointment of motion pictures dependent on a few important qualities with respect to system by systematically analyzing decision tree algorithms. The weightage for each attribute is calculated in the first stage, and then weightage of that movie is calculated by combined calculation of attributes using decision tree algorithms. Here we are trying to implement this idea on mainly three decision tree algorithms. J48 algorithm, Random Forest, Hoeffiding tree. Here, we try to find key factors for a profitable movie. This model assists with discovering the rating of the upcoming motion picture through qualities or attributes of that movie.