Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects
Crossref DOI link: https://doi.org/10.1038/s44387-025-00033-7
Published Online: 2025-11-03
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Köhler, David
Rügamer, David
Boyle, Lindsey J.
Maloney, Kelly O.
Schmid, Matthias
Text and Data Mining valid from 2025-11-03
Version of Record valid from 2025-11-03
Article History
Received: 30 September 2024
Accepted: 9 August 2025
First Online: 3 November 2025
Competing interests
: The authors declare no competing interests.