Genetic algorithm based feature selection with ensemble methods for student academic performance prediction
Student academic performance is an important factor that affect the achievement of an educational institution. Educational Data Mining (EDM) is a data mining process that is applied to explore educational data that can produce information related to student academic performance. The knowledge produc...
Saved in:
Main Authors: | Al Farissi, Al Farissi, Mohamed Dahlan, Halina, Samsuryadi, Samsuryadi |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/92480/1/HalinaMohamedDahlan2020_GeneticAlgorithmBasedFeatureSelection.pdf http://eprints.utm.my/id/eprint/92480/ http://dx.doi.org/10.1088/1742-6596/1500/1/012110 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Genetic algorithm based feature selection for predicting student’s academic performance
by: Al Farissi, Al Farissi, et al.
Published: (2020) -
Flat role based access control and encryption scheme for database security
by: Al Farissi, Al Farissi
Published: (2013) -
Derivation of factors in dealing negative E-WOM for maintaining online reputation
by: Kurnia, Rizka Dhini, et al.
Published: (2021) -
Biomimetic pattern recognition for writer identification using geometrical moment functions
by: Samsuryadi, Samsuryadi
Published: (2013) -
Handwriting analysis for personality trait features identification using CNN
by: Alamsyah, Derry, et al.
Published: (2022)