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This project explores several Machine Learning methods to predict moviegenres based on plot summaries. Naive Bayes, Word2Vec+XGBoost and RecurrentNeural Networks are used for text classification, while K-binarytransformation, rank method and probabilistic classification with learnedprobability threshold are employed for the multi-label problem involved in thegenre tagging task.Experiments with more than 250,000 movies show thatemploying the Gated Recurrent Units (GRU) neural networks for the probabilisticclassification with learned probability threshold approach achieves the bestresult on the test set. The model attains a Jaccard Index of 50.0%, a F-scoreof 0.56, and a hit rate of 80.5%.

Predicting Movie Genres Based on Plot Summaries