Lötsch, 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 [cd], Scientific Reports. London: Macmillan Publishers Limited. doi:10.1038/s41598-023-32396-9.
Chicago Manual of Style 17th edition (full note)Lötsch, Jörn, und Alfred Ultsch. Recursive computed ABC (c ABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size. Cd. Scientific Reports. London: Macmillan Publishers Limited, [2023?], London: Macmillan Publishers Limited, [2023?]. https://doi.org/10.1038/s41598-023-32396-9.
American Psychological Association 7th editionLötsch, 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 [Cd]. In Scientific Reports. Macmillan Publishers Limited. https://doi.org/10.1038/s41598-023-32396-9
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.
ISO-690 (author-date, Deutsch)LÖTSCH, Jörn und Alfred ULTSCH, 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