Thesis supervisor: Tibor Gábor Tajti
Location of studies (in Hungarian): University of Debrecen Faculty of Informatics Abbreviation of location of studies: DEIK
Description of the research topic:
This research topic focuses on studying existing and possible new ensemble methods that can improve the efficiency of applying proven algorithms in the field of machine learning. Emphasis will be put on the specificities of the different application domains and the applicability to multiple machine learning algorithms.
Bibliography
[1] Dietterich, Thomas G. "Ensemble methods in machine learning." International workshop on multiple classifier systems. Springer, Berlin, Heidelberg, 2000.
[2] Sagi, Omer, and Lior Rokach. "Ensemble learning: A survey." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8.4 (2018): e1249.
[3] Zhou, Zhi-Hua. Ensemble methods: foundations and algorithms. Chapman and Hall/CRC, 2019.
[4] Opitz, David, and Richard Maclin. "Popular ensemble methods: An empirical study." Journal of artificial intelligence research 11 (1999) 169-198