Using Gradient Boosting for Time Series prediction tasks

Time series prediction problems are pretty frequent in the retail domain.

Companies like Walmart and Target need to keep track of how much product should be shipped from Distribution Centres to stores. Even a small improvement in such a demand forecasting system can help save a lot of dollars in term of workforce management, inventory cost and out of stock loss.

While there are many techniques to solve this particular problem like ARIMA, Prophet, and LSTMs, we can also treat such a problem as a regression problem too and use trees to solve it.

In this post, we will try to solve the time series problem using XGBoost.

The main things I am going to focus on are the sort of features such a setup takes and how to create such features.