Test Set

A test set is a collection of data used to evaluate how well a machine learning model performs. After a model is trained on previous data, the test set provides new, unseen examples to assess its accuracy and generalization—meaning its ability to make correct predictions on data it hasn't encountered before. This helps determine whether the model is reliable and effective for real-world use. The test set is a crucial step in developing and validating models to ensure they work well beyond the initial training data.