Also known as: Test dataset · Testing Data
Un conjunto de prueba es un conjunto de datos reservado usado para proporcionar una evaluación independiente de un modelo entrenado o sistema de IA. Debe separarse de los datos de entrenamiento y validación para que las estimaciones de rendimiento reflejen mejor el comportamiento sobre datos no vistos antes del despliegue o la publicación.
‘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.
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.