The conversation between human and AI assistant.
How do I compute precision and recall for a multi-class classification problem? Can I only compute accuracy?
That's good to know. Can you explain how precision and recall are different?
Sure, precision is the number of true positives divided by the sum of true positive and false positive. Recall is the number of true positives divided by the sum of true positive and false negative. Precision measures how many of the predicted positives are actually positive, while recall measures how many of the actual positives were correctly predicted.