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

Marmolejo-Ramos, Fernando; Tejo, Mauricio; Brabec, Marek; Kuzilek, Jakub; Joksimovic, Srecko; Kovanovic, Vitomir; González, Jorge; Kneib, Thomas; Bühlmann, Peter; Kook, Lucas; Briseño-Sánchez, Guillermo; Ospina, Raydonal

Marmolejo-Ramos, Fernando; Tejo, Mauricio; Brabec, Marek; Kuzilek, Jakub; Joksimovic, Srecko; Kovanovic, Vitomir; González, Jorge; Kneib, Thomas; Bühlmann, Peter; Kook, Lucas; Briseño-Sánchez, Guillermo; Ospina, Raydonal.

Afiliación

Marmolejo-Ramos F; Centre for Change and Complexity in Learning University of South Australia Adelaide Australia.
Tejo M; Instituto de Estadística Universidad de Valparaíso Valparaíso Chile.
Brabec M; Department of Statistical Modelling Institute of Computer Science of the Czech Academy of Sciences Prague Czech Republic.
Kuzilek J; Czech Institute of Informatics Robotics and Cybernetics, CTU Prague Czech Republic.
Joksimovic S; Computer Science Education/Computer Science and Society Research Group Humboldt University of Berlin Berlin Germany.
Kovanovic V; Centre for Change and Complexity in Learning University of South Australia Adelaide Australia.
González J; Centre for Change and Complexity in Learning University of South Australia Adelaide Australia.
Kneib T; Departamento de Estadística Pontificia Universidad Católica de Chile Santiago de Chile Chile.
Bühlmann P; Campus Institute Data Science (CIDAS) and Chair of Statistics Georg-August-Universität Göttingen Göttingen Germany.
Kook L; Seminar for Statistics, ETH Zürich Zürich Switzerland.
Briseño-Sánchez G; Epidemiology, Biostatistics, and Prevention Institute University of Zurich Zurich Switzerland.
Ospina R; Institute of Data Analysis and Process Design Zurich University of Applied Sciences Winterthur Switzerland.

Wiley Interdiscip Rev Data Min Knowl Discov ; 13(1): e1479, 2023.

Article en En | MEDLINE | ID: mdl-37502671

Palabras clave

causal regularization; causality; educational data mining; generalized additive models for location, scale, and shape; learning analytics; machine learning; statistical learning; statistical modeling; supervised learning

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Wiley Interdiscip Rev Data Min Knowl Discov Año: 2023 Tipo del documento: Article

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