TIFNGK_E41222719/visualize_confusion.py

24 lines
603 B
Python

import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from sklearn.metrics import confusion_matrix
data_cm = np.array([
[146, 34, 19],
[60, 36, 28],
[29, 16, 280]
])
labels = ['Negatif', 'Netral', 'Positif']
plt.figure(figsize=(8, 6))
sns.set(font_scale=1.2)
ax = sns.heatmap(data_cm, annot=True, fmt='d', cmap='Blues',
xticklabels=labels, yticklabels=labels)
plt.xlabel('Prediksi', fontsize=14, labelpad=15)
plt.ylabel('Aktual', fontsize=14, labelpad=15)
plt.title('Confusion Matrix Skenario 1 (Baseline)', fontsize=16, pad=20)
plt.show()