Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics

0563344 - ÚI 2024 RIV US eng J - Článek v odborném periodiku
Marmolejo-Ramos, F. - Tejo, M. - Brabec, Marek - Kužílek, J. - Joksimovic, S. - Kovanovic, V. - González, J. - Kneib, T. - Bühlmann, P. - Kook, L. - Briseño-Sánchez, G. - Ospina, R.
Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery. Roč. 13, č. 1 (2023), č. článku e1479. ISSN 1942-4787. E-ISSN 1942-4795
Institucionální podpora: RVO:67985807
Klíčová slova: causal regularization * causality * educational data mining * generalized additive models for location, scale and shape * learning analytics * machine learning * statistical learning * statistical modeling * supervised learning
Obor OECD: Statistics and probability
Impakt faktor: 7.8, rok: 2022
Způsob publikování: Open access
https://dx.doi.org/10.1002/widm.1479

Trvalý link: https://hdl.handle.net/11104/0335333