Machine Learning based Prediction of Dropout Students from the Education University using SMOTE
Author:
Affiliation:
1. Vels Institute of Science, Technology & Advanced Studies. (VISTAS),Department of Computer Science,Chennai,India
2. Vels Institute of Science, Technology & Advanced Studies (VISTAS),Department of Information Technology,Chennai,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9716239/9716227/09716450.pdf?arnumber=9716450
Reference36 articles.
1. Local neighbourhood extension of SMOTE for mining imbalanced data
2. SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering
3. SMOTE-RSB *: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory
4. Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection
5. Student Dropout Prediction
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