Using spatiotemporal relational random forests to improve our understanding of severe weather processes

DOI10.1002/sam.10128OpenAlexW1999317054WikidataQ109552550 ScholiaQ109552550MaRDI QIDQ4969791

Amy McGovern, Nathaniel Troutman, Jeffrey Basara, John K. Williams, David John Gagne, Rodger A. Brown

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.10128

zbMATH Keywords

random forestsstatistical relational learningsevere weatherspatiotemporal data mining

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Uses Software

• C4.5

Cites Work

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• Robust classification for imprecise environments
• Random forests

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