# Test set

> A subset of the dataset reserved for testing a trained model. Traditionally, you divide examples in the dataset into the following three distinct subsets:[^1]

A subset of the [dataset](https://wiki.g15e.com/pages/Dataset%20(machine%20learning.txt)) reserved for testing a trained [model](https://wiki.g15e.com/pages/Model%20(machine%20learning.txt)). Traditionally, you divide examples in the dataset into the following three distinct subsets:[^1]

- a [training set](https://wiki.g15e.com/pages/Training%20data.txt)
- a [validation set](https://wiki.g15e.com/pages/Validation%20set.txt)
- a test set

Each example in a dataset should belong to only one of the preceding subsets. For instance, a single example shouldn't belong to both the training set and the test set.[^1]

The training set and validation set are both closely tied to training a model. Because the test set is only indirectly associated with training, [test loss](https://wiki.g15e.com/pages/Test%20loss.txt) is a less biased, higher quality metric than [training loss](https://wiki.g15e.com/pages/Training%20loss.txt) or [validation loss](https://wiki.g15e.com/pages/Validation%20loss.txt).[^1]

## Footnotes

[^1]: https://developers.google.com/machine-learning/glossary#test-set