Restaurants Rating Prediction using Machine Learning Algorithms

Abstract

Restaurant Rating has become the most commonly used parameter for judging a restaurant for any individual. A lot of research has been done on different restaurants and the quality of food it serves. Rating of a restaurant depends on factors like reviews, area situated, average cost for two people, votes, cuisines and the type of restaurant. The main goal of this is to get insights on restaurants which people like visit and to identify the rating of the restaurant. With this article we study different predictive models like Support Vector Machine (SVM),Random forest and Linear Regression, XGBoost, Decision Tree and have achieved a score of 83% with ADA Boost.