Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin

Ana Paez Trujillo*, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, Dimitri Solomatine

*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

66 Downloads (Pure)

Fingerprint

Dive into the research topics of 'Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin'. Together they form a unique fingerprint.

Earth and Planetary Sciences

INIS

Keyphrases