Why are test sets important in machine learning?

Why are test sets important in machine learning?

Test sets are crucial because they help evaluate the model's performance on unseen data, ensuring it generalizes well.

What happens if we don't use a test set?

Without a test set, you risk overfitting, where the model performs well on training data but poorly on new data.

How do you create a good test set?

A good test set should be representative of the real-world data the model will encounter, and it should be large enough to provide reliable metrics.

Can you give an example of a test set?

Sure! In image classification, a test set might consist of a diverse set of images that the model hasn't seen during training.