How do I calculate the accuracy score in Python for my machine learning model?

How do I calculate the accuracy score in Python for my machine learning model?

You can use the accuracy_score function from the sklearn.metrics module. First, ensure you have the predictions and the true labels.

Can you show me a code example?

Sure! Here's a simple example:

from sklearn.metrics import accuracy_score

# True labels
true_labels = [0, 1, 1, 0, 1]
# Predicted labels
predicted_labels = [0, 1, 0, 0, 1]

# Calculate accuracy
accuracy = accuracy_score(true_labels, predicted_labels)
print('Accuracy:', accuracy)

What does the accuracy score represent?

The accuracy score represents the ratio of correctly predicted instances to the total instances in the dataset.