Research Article
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 |
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