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Classification of Movie Success: A Comparison of Two Movie Datasets
IEEE World AI IoT Congress (AIIoT) 2022 (2022)
  • Shreehar Joshi, Ramapo College of New Jersey
  • Eman Abdelfattah, Ramapo College of New Jersey
  • Ryan Osgood, Ramapo College of New Jersey
Abstract
This work presents a classification problem to classify a movie's success based on features of a given movie. Two movies' datasets along with features generated from web scraping are utilized to generate the training and testing datasets. Four Machine Learning classifiers are applied to these datasets: Stochastic Gradient Descent, Random Forests, LinearSVC and Extra Trees. This study compares the performance metrics for these Machine Learning models on these two movies datasets and draws conclusions based on the results.
Publication Date
2022
Citation Information
Shreehar Joshi, Eman Abdelfattah, Ryan Osgood, “Classification of Movie Success: A Comparison of Two Movie Datasets,” the 11th IEEE World AI IoT Congress (AI IoT), Virtual Conference, Seattle, USA, 6th – 9th June 2022. (Selected as the Best paper in the category of Artificial Intelligence and Machine Learning) https://ieeexplore.ieee.org/abstract/document/9817158