Best model was Logistics Regression
classification_report:
precision recall f1-score support
-1 0.92 0.96 0.94 444
0 0.98 0.98 0.98 126
1 0.94 0.86 0.90 166
2 0.91 0.89 0.90 174
accuracy 0.93 910
macro avg 0.94 0.92 0.93 910
weighted avg 0.93 0.93 0.93 910
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classification_report:
precision recall f1-score support
-1 0.92 0.94 0.93 451
0 0.94 0.92 0.93 459
accuracy 0.93 910
macro avg 0.93 0.93 0.93 910
weighted avg 0.93 0.93 0.93 910
classification_report:
precision recall f1-score support
-1 0.84 0.95 0.89 444
0 0.95 0.92 0.94 126
1 0.95 0.77 0.85 166
2 0.85 0.73 0.79 174
accuracy 0.87 910
macro avg 0.90 0.84 0.87 910
weighted avg 0.88 0.87 0.87 910
-----------------------------------------------------------
classification_report:
precision recall f1-score support
-1 0.88 0.93 0.90 451
0 0.93 0.87 0.90 459
accuracy 0.90 910
macro avg 0.90 0.90 0.90 910
weighted avg 0.90 0.90 0.90 910
classification_report:
precision recall f1-score support
-1 0.90 0.92 0.91 444
0 0.95 0.93 0.94 126
1 0.91 0.83 0.87 166
2 0.80 0.83 0.81 174
accuracy 0.89 910
macro avg 0.89 0.88 0.88 910
weighted avg 0.89 0.89 0.89 910
-----------------------------------------------------------
classification_report:
precision recall f1-score support
-1 0.92 0.92 0.92 451
0 0.92 0.92 0.92 459
accuracy 0.92 910
macro avg 0.92 0.92 0.92 910
weighted avg 0.92 0.92 0.92 910
classification_report:
precision recall f1-score support
-1 0.82 0.71 0.76 444
0 0.85 0.91 0.88 126
1 0.66 0.73 0.70 166
2 0.61 0.72 0.66 174
accuracy 0.75 910
macro avg 0.74 0.77 0.75 910
weighted avg 0.76 0.75 0.75 910
-----------------------------------------------------------
classification_report:
precision recall f1-score support
-1 0.79 0.86 0.82 451
0 0.85 0.77 0.81 459
accuracy 0.81 910
macro avg 0.82 0.81 0.81 910
weighted avg 0.82 0.81 0.81 910
