Unlabeled data has feature columns but no target column (no answers), as illustrated below:
Unlabeled data is required to generate predictions and explanations. It must have exactly the same feature columns as the training dataset but no target column. In the context of this guide, the unlabeled data used for predictions and explanations is referred to as the test dataset. Test data starts as labeled data but the label is removed for the purpose of trialing the machine learning model.
The “unseen data” that you will eventually use with your model to make predictions is also unlabeled data. Like the test dataset, unseen data must have exactly the same feature columns as the training dataset but no target column.
For examples of training, validation, and test dataset tables and how they are structured, see Section 3.4.4, “Example Data”, and Section 8.4, “Iris Data Set Machine Learning Quickstart”.