  We predict restaurant ratings from Yelp reviews based on Yelp Open Dataset.
Data distribution is presented, and one balanced training dataset is built. Two
vectorizers are experimented for feature engineering. Four machine learning
models including Naive Bayes, Logistic Regression, Random Forest, and Linear
Support Vector Machine are implemented. Four transformer-based models
containing BERT, DistilBERT, RoBERTa, and XLNet are also applied. Accuracy,
weighted F1 score, and confusion matrix are used for model evaluation. XLNet
achieves 70% accuracy for 5-star classification compared with Logistic
Regression with 64% accuracy.
