Optimised SMOTE-based Imbalanced Learning for Student Dropout Prediction

Author:

Masood Sheikh Wakie,Gogoi Munmi,Begum Shahin AraORCID

Publisher

Springer Science and Business Media LLC

Reference54 articles.

1. Bonneau, K.: What is a dropout? North Carolina Education Research Data Center (2015)

2. Sara, N.-B.; Halland, R.; Igel, C.; Alstrup, S.: High-school dropout prediction using machine learning: a danish large-scale study. ESANN 2015, 23 (2015)

3. Aayog, N.: Discussion paper: National strategy for artificial intelligence. New Delhi: NITI Aayog. Retrieved on January 1(2020), 2019–01 (2018)

4. Jordan, M.I.; Mitchell, T.M.: Machine learning: Trends, perspectives, and prospects. Science 349(6245), 255–260 (2015)

5. Masood, S.W.; Begum, S.A.: Comparison of resampling techniques for imbalanced datasets in student dropout prediction. In: 2022 IEEE Silchar Subsection Conference (SILCON), pp. 1–7 (2022). IEEE

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