Traditional ML Comparison - Balanced Dataset with SMOTE
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Logistic Regression:
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              precision    recall  f1-score   support

         DoS       0.99      0.93      0.96      8095
      Normal       0.90      0.91      0.90     11245
       Probe       0.75      0.92      0.83      2157
         R2L       0.53      0.29      0.38      1009
         U2R       0.08      0.74      0.15        38

    accuracy                           0.89     22544
   macro avg       0.65      0.76      0.64     22544
weighted avg       0.90      0.89      0.89     22544


K-Nearest Neighbors:
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              precision    recall  f1-score   support

         DoS       0.99      0.95      0.97      8095
      Normal       0.89      0.99      0.94     11245
       Probe       0.94      0.90      0.92      2157
         R2L       0.90      0.18      0.30      1009
         U2R       0.42      0.50      0.46        38

    accuracy                           0.93     22544
   macro avg       0.83      0.70      0.72     22544
weighted avg       0.93      0.93      0.92     22544


Support Vector Machine:
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              precision    recall  f1-score   support

         DoS       0.99      0.95      0.97      8095
      Normal       0.90      0.98      0.94     11245
       Probe       0.93      0.88      0.90      2157
         R2L       0.75      0.24      0.36      1009
         U2R       0.25      0.45      0.32        38

    accuracy                           0.93     22544
   macro avg       0.76      0.70      0.70     22544
weighted avg       0.92      0.93      0.92     22544


Decision Tree:
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              precision    recall  f1-score   support

         DoS       0.99      0.94      0.97      8095
      Normal       0.89      0.99      0.94     11245
       Probe       0.85      0.84      0.85      2157
         R2L       0.94      0.14      0.24      1009
         U2R       0.23      0.47      0.31        38

    accuracy                           0.92     22544
   macro avg       0.78      0.68      0.66     22544
weighted avg       0.92      0.92      0.91     22544


Naive Bayes:
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              precision    recall  f1-score   support

         DoS       0.49      0.93      0.64      8095
      Normal       0.88      0.09      0.16     11245
       Probe       0.55      0.89      0.68      2157
         R2L       0.26      0.33      0.29      1009
         U2R       0.02      0.74      0.04        38

    accuracy                           0.48     22544
   macro avg       0.44      0.59      0.36     22544
weighted avg       0.68      0.48      0.39     22544


