Comparative Study of Various Classification and Regression Techniques on Movie Datasets Using R

Abstract

The entertainment industry has been exponentially growing since its inception and is primarily well-received. Creating content, in this case, Movies has been the bread and butter of the industry and has proven extremely lucrative over the years. In this comparative study, we have picked out various Machine Learning models, viz. Classification Tree, Regression Tree, AdaBoost, SVM (Linear Kernel, Polynomial Kernel, Radial Kernel), XGBoost, Random Forest, Simple Bagging, and Naive Bayes. The Classification models are used to predict the rate of a certain movie winning the Oscar whereas the Regression model implementation estimates the average earning of a film considering the various attributes.