How does extreme point sampling affect non-extreme simulation in geographical random forest?-Reference-Cited by-同舟云学术

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How does extreme point sampling affect non-extreme simulation in geographical random forest?

Published:2024-03-08 Issue:3 Volume:17 Page:1983-1991
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Wang Hui,Chen Meixu,Wang Zhe,Huang Li,Caudill Christopher C.,Qu Shijin,Que Xiang

Funder

NSF Idaho EPSCoR Program

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s12145-024-01268-9.pdf

Reference30 articles.

1. Belgiu M, Drăguţ L (2016) Random forest in remote sensing: a review of applications and future directions. ISPRS J Photogrammetry Remote Sens 114:24–31

2. Berry BJL, Marble DF (1968) Spatial analysis: a reader in statistical geography. Prentice-Hall

3. Boukerche A, Zheng L, Alfandi O (2020) Outlier detection: methods, models, and classification. ACM Comput Surv (CSUR) 53(3):1–37

4. Brunsdon C, Fotheringham S, Charlton M (1998) Geographically weighted regression. J Royal Stat Society: Ser D 47(3):431–443

5. Brus D, De Gruijter J (1997) Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion). Geoderma 80(1–2):1–44

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