Function demo_performance_tracking

demo.py:208–248

Demo: Show how performance is tracked

()

def demo_performance_tracking():
    """Demo: Show how performance is tracked"""
    
    print("\n" + "="*80)
    print("DEMO 4: PERFORMANCE TRACKING")
    print("="*80)
    
    print("\nAgriQuant AI tracks these metrics continuously:")
    
    print("\n--- Accuracy Metrics ---")
    print("  • Forecast Accuracy: % predictions verified by USDA")
    print("    Target: >70%")
    print("  • Mean Absolute Error: Avg difference in damage estimate")
    print("    Target: <3 percentage points")
    print("  • Confidence Calibration: 80% confident = 80% accurate")
    print("    Target: >0.90")
    
    print("\n--- Error Analysis ---")
    print("  • False Positive Rate: Predicted damage, none occurred")
    print("    Target: <20%")
    print("  • False Negative Rate: Missed significant events")
    print("    Target: <10%")
    
    print("\n--- Example Performance Report ---")
    example_metrics = {
        "period": "Last 30 days",
        "total_predictions": 23,
        "verified_count": 16,
        "avg_accuracy": 0.73,
        "success_rate": 0.70,
        "mae_pct": 2.4,
        "false_positive_rate": 0.18,
        "false_negative_rate": 0.12
    }
    
    print(json.dumps(example_metrics, indent=2))
    
    print("\n--- Event Type Breakdown ---")
    print("  Freeze events: 75% accuracy (8 events)")
    print("  Hurricane threats: 71% accuracy (7 events)")
    print("  Disease pressure: 60% accuracy (5 events)")


def demo_complete_workflow():