How can I implement advanced metrics in Python?

How can I implement advanced metrics in Python?

You can use libraries like NumPy, Pandas, and Scikit-learn to implement advanced metrics. What specific metrics are you interested in?

I'm particularly interested in precision, recall, and F1 score.

Great! You can calculate precision, recall, and F1 score using Scikit-learn's metrics module. Would you like a code example?

Yes, please provide a code example.

Here's a simple example:

from sklearn.metrics import precision_score, recall_score, f1_score

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

precision = precision_score(true_labels, predicted_labels)
recall = recall_score(true_labels, predicted_labels)
f1 = f1_score(true_labels, predicted_labels)

print(f'Precision: {precision}, Recall: {recall}, F1 Score: {f1}')

This will give you the precision, recall, and F1 score based on your true and predicted labels.