Table 5.

Model performance comparison with fixed hyperparameters.

Model	Accuracy (%)	Precision (%)	Recall (%)	F1 (%)
SSA-PNN	59.14 ± 10.84	71.82 ± 13.32	41.30 ± 10.89	63.01 ± 10.51
Extreme gradient boosting	58.27 ± 11.67	65.47 ± 13.59	43.73 ± 12.18	60.15 ± 12.14
K neighbors classifier	57.43 ± 11.59	64.44 ± 13.60	43.96 ± 12.81	59.12 ± 12.04
Gradient boosting classifier	57.71 ± 11.82	66.62 ± 14.31	43.44 ± 13.05	60.04 ± 11.98
Random forest classifier	56.99 ± 11.72	66.10 ± 15.00	43.04 ± 12.98	59.32 ± 11.90
Ada boost classifier	56.97 ± 11.69	66.71 ± 14.42	42.25 ± 12.64	59.61 ± 11.78
Ridge classifier	56.69 ± 10.94	64.29 ± 12.48	39.65 ± 9.95	59.22 ± 11.15
SVM—linear kernel	56.51 ± 11.55	62.79 ± 13.44	44.32 ± 13.71	57.88 ± 11.98
Linear discriminant analysis	56.18 ± 11.24	63.24 ± 12.74	41.27 ± 12.72	58.47 ± 11.42
Logistic regression	55.44 ± 11.47	61.71 ± 13.56	43.44 ± 12.91	56.68 ± 11.97