Restaurant Rating Prediction Using Regression

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Restaurant Rating Prediction Using Regression

Somashekar, Suhas / Mallesh, Suhas

Opening a new Restaurant has been a challenge especially in current times due to tough competition and variety of choices for a consumer. Thus, Rating of a restaurant becomes an important parameter for judging the quality of a Restaurant. A good rating acts as an invitation for new customers. And every new business wishes to know if it will succeed in future or not. The purpose of this paper is to provide validation for new Restaurants about their predicted Ratings. By inputting various factors that are characteristics of a planned Restaurant, one is able to predict the average Ratings and if necessary, provide a comparison between various options of a particular characteristic of the Restaurant. It can also help one in making the right choices before the action of opening a new Restaurant is implemented. Thereby securing them against investment losses, saving time and making the whole process a well thought out calculated risk. Seven different types of regression models are used to make the predictions by considering factors that can be easily controlled before setting up a new restaurant and finally model metrics are compared to choose the best regression model for future prediction.