Lötsch, J., & Ultsch, A. [ca. 2023]. Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size. In Scientific Reports [Cd]. London: Macmillan Publishers Limited. https://doi.org/10.1038/s41598-023-32396-9
ISO-690 (author-date, English)LÖTSCH, Jörn und ULTSCH, Alfred, 2023. Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size. London: Macmillan Publishers Limited.
Modern Language Association 9th editionLötsch, J., und A. Ultsch. „Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size“. Scientific Reports, cd, Macmillan Publishers Limited, 2023, https://doi.org/10.1038/s41598-023-32396-9.
Mohr Siebeck - Recht (Deutsch - Österreich)Lötsch, Jörn/Ultsch, Alfred: Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size, London 2023.
Emerald - HarvardLötsch, J. und Ultsch, A. (2023), Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size, Scientific Reports, Bd. , Macmillan Publishers Limited, London, verfügbar unter:https://doi.org/10.1038/s41598-023-32396-9.