"test dataset" is a correct and usable phrase in written English.
It is typically used in the context of data analysis and refers to a subset of data that is used to evaluate the performance of a model or algorithm. Example: The researchers used a test dataset to validate the accuracy of their predictive model before applying it to the larger dataset.
We randomly divided the 1,500 input vectors into 1,000 as the primary test dataset and 500 as the confirmative test dataset.
Uniformity in the training and test dataset was shown to be important in deriving PTFs.
Teams were ranked based on two classification performance metrics evaluated on a blinded test dataset.
Figure 4(b) shows the confirmative test dataset, exhibiting plots of predicted versus experimental pressure for each of the 36 sectors.
The DNN modeling and the ensuing regression transformed the confirmative test dataset, and a complete coincidence was achieved between the predicted and the experimentally measured pressures.
During the analysis of these datasets we have developed several computational tools and pipelines and we have distributed these tools freely with a test dataset for wider use.
(a) Predicted vs measured displacement (pressure) curves for 1,000 test data points (primary test dataset) for each of the 36 sectors.
A wooden stick was used to generate the training dataset, but the test dataset was separately prepared using a plastic toy finger.
We actually used the test dataset produced by the same wooden bar, and the test accuracy was improved regardless of the DNN architecture.
Note that the most important point here is that the training dataset was made by a wooden bar but the test dataset was made by a toy finger.
The test dataset size was smaller than the training dataset, which involved 108,000 (1500 × 36 × 2) input vectors with labels for the 6 × 6 lattice.
