# Test Set

Similar to the training set, you will want to have your test set contain representative variations of what you expect to encounter during runtime. The key differentiation between the training set and the test set is that the test set are not included during the training of the tool. Instead, the test set are used to evaluate the results of training and thus they are also called as evaluation set. The remainder of the images that are excluded from the training set will automatically be the test set.

You will also want to label the test set in the same way that you label the training set. This will allow you to perform statistical analysis of training set, to determine how well the tool is generalizing its results.