Table 2.

Labels and levels of the different factors.

Code	Name	Values/Categories/Levels
PP	Performance parameters	25 different parameters (see table from Section 4.3)
ML	Machine learning algorithm	XGBoost, naïve Bayes, support vector machine (SVM), NN (multi-layer feed-forward of resilient backpropagation network or RPropMLP) and probabilistic neural network (PNN)
NS	Number of samples, dataset size	100, 500, 1000, and total (all samples of the balanced dataset)
SR	Split ratios for the train/test splits	50, 60, 70, 80