Table 3.

Decision matrix of alternatives.

Criteria	Accuracy	Recall	Precision	F1-Score	ROC AUC	Log Loss	Number of Training Samples Needed	Impact of Feature Scaling	Impact of Hyperparameter Tuning	Tolerance to İrrelevant Attributes
SVM	99.0%	99.0%	99.5%	99.0%	99.5%	−0.828	0.92	0.92	YES	0.92
Random Forest	97.5%	97.0%	98.0%	97.0%	99.0%	−0.815	0.75	0.08	YES	0.08
Logistic Regression	97.5%	97.0%	98.0%	97.0%	99.0%	−0.815	0.50	0.25	NO	0.50
KNN	98.0%	98.0%	98.5%	98.0%	99.0%	−0.819	0.08	0.92	YES	0.50
Naive Bayes	97.5%	97.0%	98.0%	97.0%	99.0%	−0.815	0.50	0.08	NO	0.75