# On Choice of Hyper-parameter in Extreme Value Theory based on Machine Learning Techniques

arXiv: https://arxiv.org/abs/2107.06074 · HTML: https://mlsanity.com/paper/2107.06074/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 22 references that are in the map.
- First posted on arXiv 13 Jul 2021.

## Built on by (most cited first, 1 of 1)

- [On Regression in Extreme Regions](https://mlsanity.com/paper/2303.03084/) (2023)

## Abstract (arXiv)

Extreme value theory (EVT) is a statistical tool for analysis of extreme events. It has a strong theoretical background, however, we need to choose hyper-parameters to apply EVT. In recent studies of machine learning, techniques of choosing hyper-parameters have been well-studied. In this paper, we propose a new method of choosing hyper-parameters in EVT based on machine learning techniques. We also experiment our method to real-world data and show good usability of our method.