Lötsch, J., & Mayer, B. [ca. 2022]. A biomedical case study showing that tuning random forests can fundamentally change the interpretation of supervised data structure exploration aimed at knowledge discovery. In Bio Med Informatics [Cd]. Basel: MDPI. https://doi.org/10.3390/biomedinformatics2040034

LÖTSCH, Jörn und MAYER, Benjamin, 2022. A biomedical case study showing that tuning random forests can fundamentally change the interpretation of supervised data structure exploration aimed at knowledge discovery. Basel: MDPI.

Lötsch, J., und B. Mayer. „A biomedical case study showing that tuning random forests can fundamentally change the interpretation of supervised data structure exploration aimed at knowledge discovery“. Bio Med Informatics, cd, MDPI, 2022, https://doi.org/10.3390/biomedinformatics2040034.

Lötsch, Jörn/Mayer, Benjamin: A biomedical case study showing that tuning random forests can fundamentally change the interpretation of supervised data structure exploration aimed at knowledge discovery, Basel 2022.

Lötsch, J. und Mayer, B. (2022), A biomedical case study showing that tuning random forests can fundamentally change the interpretation of supervised data structure exploration aimed at knowledge discovery, Bio Med Informatics, Bd. , MDPI, Basel, verfügbar unter:https://doi.org/10.3390/biomedinformatics2040034.