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all_models_report.txt
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all_models_report.txt
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--------------------------------------------------
The accuracy score that we get is: 0.875
--------------------------------------------------
The accuracy score that we get is: 0.875
Confusion Matrix: [[148 3]
[ 20 13]]
precision recall f1-score support
0 0.88 0.98 0.93 151
1 0.81 0.39 0.53 33
micro avg 0.88 0.88 0.88 184
macro avg 0.85 0.69 0.73 184
weighted avg 0.87 0.88 0.86 184
Total time Taken is : 0.003935000000000022
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8478260869565217
Confusion Matrix: [[147 4]
[ 24 9]]
precision recall f1-score support
0 0.86 0.97 0.91 151
1 0.69 0.27 0.39 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.62 0.65 184
weighted avg 0.83 0.85 0.82 184
Total time Taken is : 0.3605099999999999
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8695652173913043
Confusion Matrix: [[144 7]
[ 17 16]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.70 0.48 0.57 33
micro avg 0.87 0.87 0.87 184
macro avg 0.80 0.72 0.75 184
weighted avg 0.86 0.87 0.86 184
Total time Taken is : 0.017979999999999885
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8532608695652174
Confusion Matrix: [[146 5]
[ 22 11]]
precision recall f1-score support
0 0.87 0.97 0.92 151
1 0.69 0.33 0.45 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.65 0.68 184
weighted avg 0.84 0.85 0.83 184
Total time Taken is : 12.194761
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8641304347826086
Confusion Matrix: [[144 7]
[ 18 15]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.68 0.45 0.55 33
micro avg 0.86 0.86 0.86 184
macro avg 0.79 0.70 0.73 184
weighted avg 0.85 0.86 0.85 184
Total time Taken is : 0.019557999999999964
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.875
Confusion Matrix: [[148 3]
[ 20 13]]
precision recall f1-score support
0 0.88 0.98 0.93 151
1 0.81 0.39 0.53 33
micro avg 0.88 0.88 0.88 184
macro avg 0.85 0.69 0.73 184
weighted avg 0.87 0.88 0.86 184
Total time Taken is : 0.0031399999999999206
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8478260869565217
Confusion Matrix: [[147 4]
[ 24 9]]
precision recall f1-score support
0 0.86 0.97 0.91 151
1 0.69 0.27 0.39 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.62 0.65 184
weighted avg 0.83 0.85 0.82 184
Total time Taken is : 0.3105629999999999
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8695652173913043
Confusion Matrix: [[144 7]
[ 17 16]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.70 0.48 0.57 33
micro avg 0.87 0.87 0.87 184
macro avg 0.80 0.72 0.75 184
weighted avg 0.86 0.87 0.86 184
Total time Taken is : 0.015778999999999987
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8532608695652174
Confusion Matrix: [[146 5]
[ 22 11]]
precision recall f1-score support
0 0.87 0.97 0.92 151
1 0.69 0.33 0.45 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.65 0.68 184
weighted avg 0.84 0.85 0.83 184
Total time Taken is : 13.351534
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8641304347826086
Confusion Matrix: [[144 7]
[ 18 15]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.68 0.45 0.55 33
micro avg 0.86 0.86 0.86 184
macro avg 0.79 0.70 0.73 184
weighted avg 0.85 0.86 0.85 184
Total time Taken is : 0.08850699999999989
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.875
Confusion Matrix: [[148 3]
[ 20 13]]
precision recall f1-score support
0 0.88 0.98 0.93 151
1 0.81 0.39 0.53 33
micro avg 0.88 0.88 0.88 184
macro avg 0.85 0.69 0.73 184
weighted avg 0.87 0.88 0.86 184
Total time Taken is : 0.0033560000000000256
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8478260869565217
Confusion Matrix: [[147 4]
[ 24 9]]
precision recall f1-score support
0 0.86 0.97 0.91 151
1 0.69 0.27 0.39 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.62 0.65 184
weighted avg 0.83 0.85 0.82 184
Total time Taken is : 0.3036380000000001
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8695652173913043
Confusion Matrix: [[144 7]
[ 17 16]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.70 0.48 0.57 33
micro avg 0.87 0.87 0.87 184
macro avg 0.80 0.72 0.75 184
weighted avg 0.86 0.87 0.86 184
Total time Taken is : 0.01165000000000016
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8532608695652174
Confusion Matrix: [[146 5]
[ 22 11]]
precision recall f1-score support
0 0.87 0.97 0.92 151
1 0.69 0.33 0.45 33
micro avg 0.85 0.85 0.85 184
macro avg 0.78 0.65 0.68 184
weighted avg 0.84 0.85 0.83 184
Total time Taken is : 12.617932
--------------------------------------------------
--------------------------------------------------
The accuracy score that we get is: 0.8641304347826086
Confusion Matrix: [[144 7]
[ 18 15]]
precision recall f1-score support
0 0.89 0.95 0.92 151
1 0.68 0.45 0.55 33
micro avg 0.86 0.86 0.86 184
macro avg 0.79 0.70 0.73 184
weighted avg 0.85 0.86 0.85 184
Total time Taken is : 0.16913300000000042
--------------------------------------------------