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Table 7 Average performance of machine learning algorithms and logistic regression (%)

From: Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Author(s) Prediction ANN RF/DT SVM NB J48 LR
Acikkar and Akay (2009) a) 93.8
Bahadır (2016) b) 93.0 90.8
Delen (2010) c) 86.5 87.2 87.2 86.1
Delen (2011) c) 81.2 78.3 74.3
Hussain, Zhu, Zhang, and Abidi (2018) d) 85.9 82.9 88.5
Oztekin (2016) c) 71.6 73.8 77.6
Sreenivasa Rao, Swapna, and Praveen Kumar (2018) a) 100.0 61.1 88.9
Teshnizi et al. (2015) c) 84.3 77.5
  1. Algorithms: ANN Artificial neural network, RF/DT Random forest / decision tree, SVM Support vector machines, NB Naïve Bayes, J48 C4.5 decision tree, LR Logistic regression; Predictions: a) admission decisions; b) student academic performance; c) drop-out undergraduate students; d) student engagement