update, added the models and the processed folders

README.md

@@ -228,10 +228,10 @@ Alternatively, you can use Docker to run the entire system:
 
 The Random Forest model achieves the following performance metrics on the validation set:
 
-- **Accuracy**: ~99.5%
+- **Accuracy**: ~99.84%
-- **Precision**: ~95% (minimizing false positives)
+- **Precision**: ~94.78% (minimizing false positives)
-- **Recall**: ~92% (minimizing false negatives)
+- **Recall**: ~77.35% (minimizing false negatives)
-- **F1 Score**: ~93% (balance between precision and recall)
+- **F1 Score**: ~85.18% (balance between precision and recall)
 
 The most important features for fraud detection include:
 1. Transaction amount

src/config.py

@@ -22,7 +22,7 @@ MODEL_METADATA_PATH = MODELS_DIR / 'model_metadata.json'
 
 # API settings
 API_HOST = '0.0.0.0'
-API_PORT = 8000
+API_PORT = 8001
 
 # Web UI settings
 WEB_HOST = '0.0.0.0'