Comparing Correlation-Based Feature Selection and Symmetrical Uncertainty for Student Dropout Prediction
Predicting student dropout is essential for universities dealing with high attrition rates. This study compares two feature selection (FS) methods—correlation-based feature selection (CFS) and symmetrical uncertainty (SU)—in educational data mining for dropout prediction. We evaluate these methods u...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ikatan Ahli Informatika Indonesia
2024-08-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | https://jurnal.iaii.or.id/index.php/RESTI/article/view/5911 |
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