https://www.kaggle.com/c/walmart-recruiting-store-sales-forecasting
One challenge of modeling retail data is the need to make decisions based on limited history. If Christmas comes but once a year, so does the chance to see how strategic decisions impacted the bottom line.
We are provided with historical sales data for 45 Walmart stores located in different regions. Each store contains many departments, and participants must project the sales for each department in each store. To add to the challenge, selected holiday markdown events are included in the dataset. These markdowns are known to affect sales, but it is challenging to predict which departments are affected and the extent of the impact.
We need to predict the final sales in the week given the features.
All the documented code with detailed instructions is in the python notebook.
Used weighted mean absolute error (WMAE) for evaluation metric:
Public LB- 2732.9 Private LB- 2882.5