How can I visualize a confusion matrix?

How can I visualize a confusion matrix?

You can visualize a confusion matrix using libraries like Matplotlib or Seaborn in Python. Would you like a code example?

Yes, please provide a code example using Python.

Sure! Here's a simple example:

import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import confusion_matrix

# Sample data
true_labels = [0, 1, 0, 1, 0, 1]
predicted_labels = [0, 0, 1, 1, 0, 1]

# Create confusion matrix
cm = confusion_matrix(true_labels, predicted_labels)

# Visualize
plt.figure(figsize=(8, 6))
sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')
plt.xlabel('Predicted labels')
plt.ylabel('True labels')
plt.title('Confusion Matrix')
plt.show()

What do the values in the confusion matrix represent?

The values represent the counts of true positives, true negatives, false positives, and false negatives, helping you evaluate model performance.