Skip to content

Latest commit

 

History

History
9 lines (8 loc) · 612 Bytes

README.md

File metadata and controls

9 lines (8 loc) · 612 Bytes

This repository contains the code to reproduce the results from the blog post A New Method for Multi-Horizon Forecasting with a Single Tree-based Model.

  1. Download the data.
  2. Add calendar.csv and sales_train_validation.csv to data/.
  3. Make a virtual environment with Python 3.11.
  4. Install the requirements with pip install -r requirements.txt.
  5. Run feature-engineering.ipynb to generate data/features.parquet.
  6. Run cross-validation.ipynb to run the cross validation.
  7. Run make-plots.ipynb to make the plots.