Predicting Restaurant Rating using Machine Learning and comparison of Regression Models

The restaurant industry is one of the prevailing competitive sectors. People enjoy cherishing communal dining for centuries, hence the demand for restaurants increasing day by day. Bangalore is a heaven for foodies with a range of cuisines from different parts of the world. In this paper, the data set for restaurants for a specific location is identified and the Data Visualization tools are applied to understand the trends and patterns of the food culture. This paper proposes a model to understand the factors affecting the rating of restaurants. Machine learning and predictive analytics with wide spread range of tools and techniques aids to predict the rating of restaurants. In this paper model is built using various regression algorithms and the most efficient algorithm is considered. The result of this paper helps new restaurants in deciding their menu, cuisine, theme, cost, demographic location etc. thereby increasing the business.