What are the different types of AI training metrics?

What are the different types of AI training metrics?

AI training metrics can be categorized into several types, including accuracy, precision, recall, F1 score, and loss.

Can you explain accuracy and how it's calculated?

Accuracy measures the proportion of correct predictions made by the model. It's calculated as the number of correct predictions divided by the total number of predictions.

What about precision and recall? How do they differ?

Precision measures the accuracy of positive predictions, while recall measures the ability to find all relevant instances. They are often used together to evaluate model performance.

Why is the F1 score important?

The F1 score is important because it balances precision and recall, providing a single metric that reflects both aspects of model performance.