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

Author(s)	Mareena Fernandes, Robin Lobo
Country	India
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.
Keywords	Classification, Regression, Machine Learning, Classification Tree, Regression Tree, SVM (Support Vector Machine), Linear Kernel, Polynomial Kernel, Radial Kernel, AdaBoost, XGBoost, Random Forest, Simple Bagging, Naive Bayes, MAE, MSE
Field	Computer > Data / Information
Published In	Volume 5, Issue 4, July-August 2023
Published On	2023-08-22
Cite This	Comparative Study of Various Classification and Regression Techniques on Movie Datasets Using R - Mareena Fernandes, Robin Lobo - IJFMR Volume 5, Issue 4, July-August 2023. DOI 10.36948/ijfmr.2023.v05i04.5660
DOI	https://doi.org/10.36948/ijfmr.2023.v05i04.5660
Short DOI	https://doi.org/gsm4ws

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International Journal For Multidisciplinary Research