A predictive model to forecast the cost for 2 people to dine in a Bangalore restaurant.
This dataset contains information about the restaurants in multiple locations across Bangalore. The information includes the restaurant types, the variety of food choices available, the approximate cost for two people in a particular restaurant, etc. Also, the key factors that indicate the success quotient of a restaurant like rating, number of people who've caused the rating have also been listed in the dataset. Details about facilities like online order, advanced booking of tables has also been provided.
- Linear Regression
- XGBoost
- Random Forest
- Multilayer Perceptron
- Support Vector Regression
Random Forest Regressor outperformed all the other machine learning models and generalized well across training and testing data. For further insight, please head over to the jupyter notebook.
- Rajesh Kumar Gupta Lakshminarayan Gupta
- Vishaali Kadambur Srikanth