Gradient boosting with extreme-value theory for wildfire prediction

@article{Koh2021GradientBW,
  title={Gradient boosting with extreme-value theory for wildfire prediction},
  author={Jonathan Koh},
  journal={Extremes},
  year={2021},
  pages={1-27}
}
  • Jonathan Koh
  • Published 18 October 2021
  • Computer Science
  • Extremes
This paper details the approach of the team Kohrrelation in the 2021 Extreme Value Analysis data challenge, dealing with the prediction of wildfire counts and sizes over the contiguous US. Our approach uses ideas from extreme-value theory in a machine learning context with theoretically justified loss functions for gradient boosting. We devise a spatial cross-validation scheme and show that in our setting it provides a better proxy for test set performance than naive cross-validation. The… 
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