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Extremal Random Forests
Journal of the American Statistical Association ( IF 3.7 ) Pub Date : 2024-01-08 , DOI: 10.1080/01621459.2023.2300522
Nicola Gnecco 1, 2 , Edossa Merga Terefe 2, 3 , Sebastian Engelke 2
Affiliation  

Classical methods for quantile regression fail in cases where the quantile of interest is extreme and only few or no training data points exceed it. Asymptotic results from extreme value theory can...

中文翻译:

极值随机森林

当感兴趣的分位数极端并且只有很少或没有训练数据点超过它时,分位数回归的经典方法会失败。极值理论的渐近结果可以...
更新日期:2024-01-08
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