On Choice of Hyper-parameter in Extreme Value Theory based on Machine Learning Techniques
Machine Learning
2021-07-14 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2107.06074,
title = {On Choice of Hyper-parameter in Extreme Value Theory based on Machine Learning Techniques},
author = {Chikara Nakamura},
journal= {arXiv preprint arXiv:2107.06074},
year = {2021}
}