DATA MINING APPROACH FOR PREDICTING STUDENT PERFORMANCE

By Edin Osmanbegović, Mirza Suljić. 2012

353 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7667fc589eca6c741b1fd5435d8593cc64f319bc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Nazar Zaki
2. Kwetishe Joro Danjuma
3. Balqis Albreiki
4. Hany Alashwal

Citations in the corpus

• A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques (2021, background): “Osmanbegovic et al. [24] analyze Naive Bayes (NB), Decision Tree (DT), and Multilayer perception (MLP) algorithms to predict students’ success.”
• Performance Evaluation of Machine Learning Algorithms in Post-operative Life Expectancy in the Lung Cancer Patients (2015, methodology): “MLP is most suitable for approximating a classification function, and consists of a set of sensory elements that make up the input layer, one or more hidden layers of processing elements, and the output layer of the processing elements [5].”