Right now, deciding when and where to open new restaurants is largely a subjective process based on the personal judgement and experience of development teams. This subjective data is difficult to accurately extrapolate across geographies and cultures.
New restaurant sites take large investments of time and capital to get up and running. When the wrong location for a restaurant brand is chosen, the site closes within 18 months and operating losses are incurred.
I prepared a notebook to solve this problem In this repo
Dataset:
Download Dataset from Kaggle: https://www.kaggle.com/c/restaurant-revenue-prediction/data
Algorithms:
Used 3 algorithms:
GradientBoostingRegressor
LinearRegression
XGBRegressor - Best results
Results:
RMS value before feature selection using XGBRegressor: 2541478.2
RMS value after feature selection using XGBRegressor: 1476119.9