Testing and validating two morphological flare predictors by logistic regression machine learning

Korsos, M.B., Erdelyi, R. orcid.org/0000-0003-3439-4127, Liu, J. et al. (1 more author) (2021) Testing and validating two morphological flare predictors by logistic regression machine learning. Frontiers in Astronomy and Space Sciences, 7. 571186. ISSN 2296-987X

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2021 Korsós, Erdélyi, Liu and Morgan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: morphological parameters; validation; binary logistic regression; machine learning; flare prediction
Dates:
  • Accepted: 11 December 2020
  • Published (online): 18 January 2021
  • Published: January 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Funding Information:
FunderGrant number
Science and Technology Facilities CouncilST/M000826/1
The Royal SocietyIE161153
Depositing User: Symplectic Sheffield
Date Deposited: 18 Jan 2021 14:12
Last Modified: 09 Nov 2021 17:06
Status: Published
Publisher: Frontiers Media
Refereed: Yes
Identification Number: https://doi.org/10.3389/fspas.2020.571186
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