Yelp provides academic students access to their data to use it in an innovative way and break ground in research. In this project, we target on the business reviews and star rating for restaurants only. We are trying to identify the key attributes or features that the consumer is looking for their best dining experience. We are using three different algorithms such as logistic regression, random forest and principal component analysis to create our models. After analyzing the performance of each models, the best model for predicting the ratings from reviews and star rating is the random forest algorithm, which exhibited an accuracy of 82%, which is better than the other algorithms that we used in this project.
Please go through the Project Report pdf which shared in this repo.