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Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-4947-2021
https://doi.org/10.5194/hess-25-4947-2021
Research article
 | 
09 Sep 2021
Research article |  | 09 Sep 2021

Development of a Wilks feature importance method with improved variable rankings for supporting hydrological inference and modelling

Kailong Li, Guohe Huang, and Brian Baetz

Data sets

Hourly data from surface meteorological stations in China China Meteorological Data Service Center http://data.cma.cn/en/?r=data/detail&dataCode=A.0012.0001

Data for "Gaining Hydrological Insights Through Wilk's Feature Importance: A Test-Statistic Interpretation method for Reliable and Robust Inference" Kailong Li https://doi.org/10.5281/zenodo.4387068

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We proposed a test statistic feature importance method to quantify the importance of predictor...
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