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Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics
- 1.0563344 - ÚI 2024 RIV US eng J - Journal Article
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
Institutional support: RVO:67985807
Keywords : causal regularization * causality * educational data mining * generalized additive models for location, scale and shape * learning analytics * machine learning * statistical learning * statistical modeling * supervised learning
OECD category: Statistics and probability
Impact factor: 6.4, year: 2023 ; AIS: 2.979, rok: 2023
Method of publishing: Open access
Result website:
https://dx.doi.org/10.1002/widm.1479DOI: https://doi.org/10.1002/widm.1479
Permanent Link: https://hdl.handle.net/11104/0335333File Download Size Commentary Version Access 0563344-aoaonl.pdf 3 3.6 MB OA CC BY 4.0 Publisher’s postprint open-access
Number of the records: 1