Universiti Teknologi Malaysia Institutional Repository

An heuristic feature selection algorithm to evaluate academic performance of students

Ajibade, S. S. M. and Ahmad, N. B. and Shamsuddin, S. M. (2019) An heuristic feature selection algorithm to evaluate academic performance of students. In: 10th IEEE Control and System Graduate Research Colloquium, ICSGRC 2019, 2-3 Aug 2019, Shah Alam, Malaysia.


Official URL: http://dx.doi.org/10.1109/ICSGRC.2019.8837067


The value of schooling and academic performance of student is the topmost priority of all academic institutions. Educational Data Mining (EDM) is an evolving area of research which aids academic institutions to enhance their student's performances. Feature Selection algorithms eradicates inapt and unrelated data from the dataset, thereby increasing the classifiers performances that are utilized in EDM. This aim of this paper is to evaluate the performance of students utilizing a heuristic technique known as Differential Evolution for feature selection algorithms on the dataset of students and some other feature selection algorithms have also been used which have never been used before on the dataset. Also, classification techniques such as Naïve Bayes (NB), Decision Tree (DT), K-Nearest Neighbor (KNN) and Discriminant Analysis (DISC) were used to evaluate. The Differential Evolution (DE) algorithm is proposed as a better feature selection algorithm for evaluating the academic performance of students and this gave a better accuracy than other feature selection algorithm that were used. The outcome of the different feature selection algorithms and classification techniques will help researchers to find the finest combinations of the classifiers and feature selection algorithms. This paper is a step towards playing an important role in enhancing the standard of education in academic institutions and also to carefully guide researchers in strategically interfering in academic issues.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:classification algorithm, differential evolution, educational data mining
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:90771
Deposited By: Narimah Nawil
Deposited On:30 Apr 2021 22:30
Last Modified:30 Apr 2021 22:30

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