Publication | Closed Access
Movie Success Prediction Using ML
19
Citations
7
References
2020
Year
Unknown Venue
EngineeringMachine LearningText MiningClassification MethodData ScienceData MiningPattern RecognitionSuccess RatePrediction ModellingPrediction MarketMachine Learning ModelPredictive AnalyticsKnowledge DiscoveryIntelligent ClassificationComputer ScienceDeep LearningPredictive LearningData ClassificationImdb DatasetClassifier SystemRandom Forest
Movies continue to be a major source of entertainment in any country. However, this industry also incurs a lot of losses when the movie does not perform at the Box Office. Our solution will try to predict the success rate of a movie by doing predictive analysis on the various features of the movie. Our model will predict the Success, based on different attributes / features of the movie. i.e. Movie crew (including director producer, music director), Movie plot (Storyline), Box-Office revenue, Audience and Critics reviews / ratings. In this paper a detailed study of machine learning algorithms such as Random Forest, DecisionTree, K-NearestNeighbours (KNN), NLP, XGBoost Classifier and Deep Neural Network were done and were implemented on IMDB dataset for predicting Success of movies. Based on the results, XGBoost Classifier gave best accuracy.
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