Also known as: Test dataset · Testing Data
Un jeu de test est un jeu de données réservé utilisé pour fournir une évaluation indépendante d’un modèle entraîné ou d’un système d’IA. Il doit être séparé des données d’entraînement et de validation afin que les estimations de performance reflètent mieux le comportement sur des données inédites avant le déploiement ou la publication.
‘data used to assess the performance of a final model’ ISO/IEC 22989.
A subset of the dataset reserved for testing a trained model. Traditionally, you divide examples in the dataset into the following three distinct subsets: - a training set - a validation set - 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. 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 is a less biased, higher quality metric than training loss or validation loss. See Datasets: Dividing the original dataset in Machine Learning Crash Course for more information.
Data used for providing an independent evaluation of the AI system in order to confirm the expected performance of that system before its placing on the market or putting into service.
A side-by-side comparison of Training Data and Test Set. Understand why the data used to fit a model must be separated from the reserved data used to evaluate it.
A side-by-side comparison of Validation Data and Test Set. Understand why development tuning data must remain separate from independent evaluation data.
A side-by-side comparison of Test Set and Holdout Data. Understand how a reserved test set relates to the broader category of data excluded from training for validation or evaluation.