I know the differences between training, validation and test data. Just to be clear
- "training data" is used to make multiple models with different hyperparameters
- "validation data" is used to choose one of these models
- "test data" is used to ascertain how well the chosen model is really doing
or to quote "Ripley, B.D. (1996) Pattern Recognition and Neural Networks, Cambridge: Cambridge University Press, p. 354":
Training set: A set of examples used for learning, that is to fit the parameters [i.e., weights] of the classifier.
Validation set: A set of examples used to tune the hyperparameters [i.e., architecture, not weights] of a classifier, for example to choose the number of hidden units in a neural network.
Test set: A set of examples used only to assess the performance [generalization] of a fully-specified classifier.
Now let's assume I am already done with the whole modelling process, I got my model and have put it into production (e.g. to classify products on an assembly line in a manufacturer). What do I call the data that is now classified? I am not using it for testing, as I am not getting any model statistics from it - it does not have labels - but I am applying my model to it.
If there is not already a word for it, and idea might be classificand, modelland or something similar, since "-end" or "-and" are suffixes forming nouns denoting patients or recipients of actions, such as addend, subtrahend, and dividend., but I was actually going more for something like "... data".
PS: rand on Why is it called "validation" dataset? I feel that is misleading name. "tuning" dataset would be more appropriate, because that is what it is used for. The "test data" is currently used for actual validation. rand off