Efficient hyperparameter tuning for predicting student performance with Bayesian optimization

Author:

Albahli SalehORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference40 articles.

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2. Uljens M (2007) JV Snellman ja pedagogisen paradoksin ratkaisu. Kasvatus 38(1):7–16

3. GPFE, ‘Global Partnership for Education’, 1999. globalpartnership.org/education (accessed Nov. 22, 2019)

4. U. I. for S. The World Bank Data, ‘Cumulative Drop-Out Rate To The Last Grade Of Lower Secondary General Education, Both Sexes (%)’, Dec. 2020. [Online]. Available: https://datacatalog.worldbank.org/cumulative-drop-out-rate-last-grade-lower-secondary-general-education-both-sexes. Accessed 02 Dec 2020

5. Asif R, Merceron A, Ali SA, Haider NG (2017) Analyzing undergraduate students’ performance using educational data mining. Comput Educ 113:177–194. https://doi.org/10.1016/j.compedu.2017.05.007

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