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Bagging-based Positive–Unlabeled Data Learning Algorithm with Base Learners Random Forest and XGBoost for 3D Exploration Targeting in the Kalatongke District, Xinjiang, China

Crossref DOI link: https://doi.org/10.1007/s11053-023-10170-y

Published Online: 2023-02-16

Published Print: 2023-04

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gao, Meng

Wang, Gongwen https://orcid.org/0000-0002-0141-7209
Yang, Wangdong

Zhang, Zhiqiang

Cai, Dingzhou

Xu, Yunchou

Yang, Shuren
Funding

Funding for this research was provided by:

Key Technologies Research and Development Program (2017YFC0601200)
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Text and Data Mining valid from 2023-02-16

Version of Record valid from 2023-02-16
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Article History

Received: 1 September 2022

Accepted: 31 January 2023

First Online: 16 February 2023

Declarations

:

: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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