Table 18 Results of classifiers (in %) with PCA.

Classifier	Training accuracy	Testing Accuracy	Precision	Sensitivity	Specificity	F1 score	AUC
LR	77.4	78.6	79	83	73	81	83
DT	83.2	78.6	72	49	79	80	83
RF	80.7	80.7	81	85	76	83	88
KNN	82.3	74.8	76	79	69	78	80
SVM	79	78.1	78	84	71	81	83
GNB	77.4	77.3	77	83	70	80	83
XGBoost	99.6	83.6	87	82	85	85	91
AdaBoost	81	76.9	79	79	74	79	86
SGD	70.7	68.9	84	54	87	66	81
GB	96.9	84.5	86	86	82	86	90
ETC	80.9	79.8	82	81	79	82	87
CatBoost	81.6	75.6	95	59	96	73	92
LightGBM	82.5	76.1	93	61	94	74	92
MLP	76.5	75.6	82	72	80	76	82
RNN	79.6	77.3	86	45	91	59	68
LSTM	82.9	79.8	87	51	91	64	71
GRU	82.4	79.4	85	43	90	58	67
Bi-LSTM	82.8	80.3	85	46	90	60	68
Bi-GRU	79	76.5	87	80	91	63	70
CNN	81.3	78.8	86	52	91	61	72
Hybrid Model	81.3	79.4	87	45	92	59	87

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