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0f755ec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | import numpy as np
import matplotlib.pyplot as plt
# --- FINAL CONFIRMED SCORES ---
results = {
"Deep Learning (CNN)": 0.7770,
"Quantum (Standard)": 0.7994,
"Classical (RF Baseline)": 0.9120,
"Quantum (Residual Specialist)": 0.6532,
"Ensemble (RF + Quantum)": 0.9154
}
# Sort for the graph
sorted_results = dict(sorted(results.items(), key=lambda item: item[1]))
print("🚀 GENERATING FINAL VICTORY ARTIFACTS...")
# 1. THE BAR CHART
plt.figure(figsize=(12, 6))
# Colors: Gray for failures, Blue for Baseline, Green for Specialist, Gold for WIN
colors = ['gray', 'gray', 'gray', 'blue', 'gold']
# We need to map these colors to the sorted keys, which might change order
# Let's assign colors manually based on the key name for safety
bar_colors = []
for key in sorted_results.keys():
if "Ensemble" in key: bar_colors.append('#FFD700') # Gold
elif "Baseline" in key: bar_colors.append('#1f77b4') # Blue
elif "Specialist" in key: bar_colors.append('#2ca02c') # Green
else: bar_colors.append('#d62728') # Red/Gray
bars = plt.barh(list(sorted_results.keys()), list(sorted_results.values()), color=bar_colors)
# Add labels
for bar in bars:
width = bar.get_width()
# Bold the winner
weight = 'bold' if width > 0.9120 else 'normal'
plt.text(width + 0.005, bar.get_y() + bar.get_height()/2, f'{width:.4f}',
va='center', fontsize=12, fontweight=weight)
plt.title("Final Result: Quantum Residual Learning Boosts SOTA", fontsize=14, fontweight='bold')
plt.xlabel("AUC Score (Higher is Better)")
plt.xlim(0.6, 0.95) # Zoom in to show the difference
plt.axvline(x=0.9120, color='blue', linestyle='--', alpha=0.5, label='Classical Ceiling (0.9120)')
plt.legend(loc='lower right')
plt.grid(axis='x', alpha=0.3)
plt.tight_layout()
plt.savefig('final_victory_chart.png')
print("📸 Saved 'final_victory_chart.png'")
print("\n✅ PROJECT COMPLETE.")
print(f" Final Boost: +{0.9154 - 0.9120:.5f} AUC") |