Student Performance Prediction Using Machine Learning Algorithms

Table 2

Optimal parameters for each algorithm.

Algorithm	Hyperparameter	Best value used
Decision trees	Maximum depth	7
	Minimum samples split	2
Naïve bayes	Smoothing parameter	1.0
K-nearest neighbors	Number of neighbors	10
	Weight function	“Distance”
Support vector machine (SVM)	Kernel	rbf
	Regularization parameter (C)	10
	Gamma	0.01