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Kaggle forecasting competitions: An overlooked learning opportunity

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  • Bojer, Casper Solheim
  • Meldgaard, Jens Peder

Abstract

We review the results of six forecasting competitions based on the online data science platform Kaggle, which have been largely overlooked by the forecasting community. In contrast to the M competitions, the competitions reviewed in this study feature daily and weekly time series with exogenous variables, business hierarchy information, or both. Furthermore, the Kaggle data sets all exhibit higher entropy than the M3 and M4 competitions, and they are intermittent.

Suggested Citation

  • Bojer, Casper Solheim & Meldgaard, Jens Peder, 2021. "Kaggle forecasting competitions: An overlooked learning opportunity," International Journal of Forecasting, Elsevier, vol. 37(2), pages 587-603.
    • Handle: RePEc:eee:intfor:v:37:y:2021:i:2:p:587-603
    DOI: 10.1016/j.ijforecast.2020.07.007
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    References listed on IDEAS

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