Question

Could you provide an example code snippet to calculate a confusion matrix in Python?

Answer 1

Certainly! Here's an example code snippet using scikit-learn to calculate a confusion matrix:

from sklearn.metrics import confusion_matrix

# Ground truth labels
actual_labels = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0]

# Predicted labels from the model
predicted_labels = [1, 0, 1, 1, 0, 0, 1, 0, 0, 0]

# Calculate confusion matrix
cm = confusion_matrix(actual_labels, predicted_labels)

print(cm)
 

Output:

[[3 2]
 [3 2]]
 

In this example, we have two classes: 0 and 1. The confusion matrix shows that there are 3 true positives (class 1 predicted as class 1), 2 false positives (class 0 predicted as class 1), 3 false negatives (class 1 predicted as class 0), and 2 true negatives (class 0 predicted as class 0).