Cross-validation results using AUC and TSS to compare the performance of different models.

<p>Each crossing symbol indicates the mean and variance of AUC and TSS tests for model replicates. All AUC and TSS result are above dashed line (slope = 1). Abbreviations are as follows. Classification Tree Analysis: CTA, Flexible Discriminant Analysis: FDA, Gradient Boosted Machine Learning:...

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Bibliographic Details
Main Author:	Yixin Diao (11280195) (author)
Other Authors:	Yue Weng (9290009) (author), Qianqian Zhao (712029) (author), Xiangxue Hu (21722180) (author), Xiaofeng Zhang (172446) (author), Bojian Gu (21722183) (author), Yihan Wang (668133) (author), Zhuojin Zhang (21722186) (author), Fang Wang (105926) (author)
Published:	2025
Subjects:	Ecology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified relatively feasible based optimal elevation range one key factor contemporary management plans conducted gap analysis combined field data allocate limited resources ailuropoda melanoleuca </ adequate forest coverage giant panda (< applied multiple criteria support future management potential habitat corridors integrated modeling approach first conducted habitat anthropogenic interference status giant pandas inside prioritize conservation actions div >< p 2 </ sup using multiple criteria giant pandas anthropogenic criteria suitable habitat habitat fragmentation future conditions corridor modeling anthropogenic metrics work provides vulnerable species term success sensed landscape innovative framework identified 34 highest priority generic methodology critical locations conservation planning 486 km
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Cross-validation results using AUC and TSS to compare the performance of different models.

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