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import numpy as np import seaborn as sns import matplotlib.pyplot as plt # Define the values for the confusion matrix true_positive = 50 true_negative = 78 false_positive = 43 false_negative = 48 # Create the confusion matrix conf_matrix = np.array([[true_positive, false_negative], [false_positive, true_negative]]) # Plot the confusion matrix using Seaborn plt.figure(figsize=(6, 5)) sns.heatmap(conf_matrix, annot=True, fmt="d", cmap="Blues", xticklabels=["Predicted Positive", "Predicted Negative"], yticklabels=["Actual Positive", "Actual Negative"]) # Title and labels plt.title("Confusion Matrix") plt.xlabel("Predicted") plt.ylabel("Actual") plt.show()
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