Frequency, Percentage and Group Percentage based on columns 'class, Predicted_class':
  class Predicted_class  Frequency  Percentage  Group_Percentage
0   neg             neg      15608    97.55000         99.891200
3   neg             pos         17     0.10625          0.108800
2   pos             neg         91     0.56875         24.266667
1   pos             pos        284     1.77500         75.733333

Computing Classification Metrics:

Target Column Value Mapping:
{'neg': 0, 'pos': 1}

Accuracy: 0.99325
ROC AUC Score: 0.8781226666666667
Precision: 0.9435215946843853
Recall: 0.7573333333333333
F1 Score: 0.8402366863905324

Confusion Matrix:
[[15608    17]
 [   91   284]]

Classification Report:
              precision    recall  f1-score   support

           0   0.994203  0.998912  0.996552     15625
           1   0.943522  0.757333  0.840237       375

    accuracy                       0.993250     16000
   macro avg   0.968863  0.878123  0.918394     16000
weighted avg   0.993016  0.993250  0.992889     16000


Done.
Processing data completed.
Time Taken: 4.797 seconds

Cost computed from Confusion Matrix:
Cost 17*500 + 91*10 = 8500 + 910 = 9410