SN	Final Estimator	LR	LR	LR	LR	LR	LR	LR	AB	BC
SN	Classifications Methods	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9	Precision (%)	Recall (%)	F1 Score (%)	Accuracy (%)
1	Extra Trees										88	96	92	91.47
2	Gradient Boosting										92	92	92	91.79
3	Logistic Regression (LR)										94	92	93	93.13
4	Passive Aggressive										95	96	96	95.89
5	SGD										95	93	94	94.00
6	Perceptron										94	94	94	94.23
7	Ridge										95	94	95	94.71
8	LinearSVC										96	95	95	95.50
9	Random Forest										91	94	93	92.59
10	AdaBoost (AB)										89	87	88	88.31
11	Decision Tree										82	85	83	83.10
12	SVC Classifier										50	100	66	49.80
13	Bagged Classifier (BC)										0	0	0	50.19
14	KNeighborsClassifier										99	13	23	57.00
15	Model (version 1)										95	96	96	95.65
16	Model (version 2)										95	96	96	95.73
17	Model (version 3)										94	94	94	94.08
18	Model (version 4)										95	97	96	95.97
19	Model (version 5)										95	97	96	95.97
20	Model (version 6)										96	97	96	96.13
21	Model (version 7)										96	97	96	96.13
22	Model (version 8)										95	96	95	95.42
23	Model (version 9)										95	95	95	95.34