40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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scenarios = ['Skenario 1\n(Baseline)', 'Skenario 2\n(Tuned)', 'Skenario 3\n(Full Optimized)']
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accuracy = [0.78, 0.79, 0.77]
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macro_f1 = [0.65, 0.66, 0.66]
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recall_netral = [0.31, 0.33, 0.37]
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x = np.arange(len(scenarios))
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width = 0.25
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fig, ax = plt.subplots(figsize=(10, 6))
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rects1 = ax.bar(x - width, accuracy, width, label='Accuracy', color='#3498db')
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rects2 = ax.bar(x, macro_f1, width, label='Macro Avg F1-Score', color='#2ecc71')
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rects3 = ax.bar(x + width, recall_netral, width, label='Recall Netral', color='#e74c3c')
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ax.set_ylabel('Scores')
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ax.set_title('Perbandingan Performa Model XGBoost antar Skenario')
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ax.set_xticks(x)
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ax.set_xticklabels(scenarios)
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ax.legend(loc='lower right')
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ax.set_ylim(0, 1.0)
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def autolabel(rects):
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for rect in rects:
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height = rect.get_height()
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ax.annotate(f'{height:.2f}',
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xy=(rect.get_x() + rect.get_width() / 2, height),
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xytext=(0, 3),
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textcoords="offset points",
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ha='center', va='bottom')
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autolabel(rects1)
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autolabel(rects2)
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autolabel(rects3)
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plt.tight_layout()
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plt.grid(axis='y', linestyle='--', alpha=0.7)
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plt.show() |