  This project explores several Machine Learning methods to predict movie
genres based on plot summaries. Naive Bayes, Word2Vec+XGBoost and Recurrent
Neural Networks are used for text classification, while K-binary
transformation, rank method and probabilistic classification with learned
probability threshold are employed for the multi-label problem involved in the
genre tagging task.Experiments with more than 250,000 movies show that
employing the Gated Recurrent Units (GRU) neural networks for the probabilistic
classification with learned probability threshold approach achieves the best
result on the test set. The model attains a Jaccard Index of 50.0%, a F-score
of 0.56, and a hit rate of 80.5%.
